MCBOpen Access

Open Access

Article

The application of the SPOC teaching model in college elective basketball courses: integrating biomechanical principles for enhanced performance

Mingming Si

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 734 , 2025, DOI: 10.62617/mcb734

Abstract：

The SPOC (Small Private Online Course) model is a new teaching model derived from Massive Open Online Courses (MOOC) and is an important direction for the reform and innovation of future higher education. In the practical application of SPOC teaching, subjectivity issues may arise, namely the influence of individual opinions and judgment criteria. The evaluation may focus on certain aspects and neglect others, resulting in incomplete overall assessment results. This paper applies the SPOC teaching model in three time periods: before class, during class, and after class, with a focus on integrating biomechanical principles into the evaluation of student performance in basketball. The study employs various research methods such as literature review, Analytic Hierarchy Process (AHP) analysis, and fuzzy comprehensive evaluation to construct a comprehensive evaluation index system for student ability improvement in SPOC teaching in higher education. This system incorporates biomechanical factors such as movement efficiency, force production, and body mechanics, which are essential for enhancing basketball skills. Based on this, an evaluation method for student ability improvement in college SPOC elective basketball courses is proposed using the AHP-fuzzy evaluation model. This model not only assesses traditional skill metrics but also integrates biomechanical assessments, such as shooting mechanics, dribbling efficiency, and defensive posture. The application of the AHP-fuzzy evaluation model, enhanced with biomechanical insights, demonstrates that his method can effectively improve students basketball abilities. The incorporation of biomechanical principles allows for a more holistic evaluation of student performance, emphasizing the importance of physical mechanics in skill development. The integration of the SPOC teaching model with biomechanical principles in elective basketball courses provides a comprehensive framework for evaluating and improving student performance. By focusing on both skill acquisition and biomechanical efficiency, this approach not only enhances basketball abilities but also fosters a deeper understanding of the physical demands of the sport.

Open Access

Article

MiR-6747-5p suppresses angiogenesis in esophageal squamous cell carcinoma by targeting EGFL6

Jiawen Huang, Yuxin Xiao, Cunjie Li, Shifeng Liu, Jieling Zhou, Qifang Song, Ting Wang, Ning Deng

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1047 , 2025, DOI: 10.62617/mcb1047

Abstract：

Epidermal growth factor-like domain 6 (EGFL6) plays a crucial role in angiogenesis in various malignant tumors. This study aimed to screen microRNAs (miRNAs) targeting EGFL6 and explore their mechanisms in regulating angiogenesis in esophageal squamous cell carcinoma (ESCC) cells. After analyzing the miRNA expression profiles of ESCC and using the target prediction algorithm, we screened three miRNAs that could potentially target EGFL6. By dual luciferase reporter gene assay and western blot, we found that miR-6747-5p could directly target EGFL6 and down-regulate EGFL6 expression in ESCC cells. The results of clone formation, CCK-8, Transwell, wound healing, and endothelial cell tube formation assay showed that miR-6747-5p exerted a significant inhibitory effect on the proliferation, migration, invasion, and angiogenesis of ESCC cells. At the same time, we observed that the phosphorylation levels of AKT and MAPK were decreased, the epithelial-mesenchymal transition (EMT) related E-cadherin expression was downregulated while N-cadherin was upregulated, and the protein expression of the pro-angiogenic factors, including platelet-derived growth factor subunit B (PDGFB), fibroblast growth factor 2 (FGF2), and angiogenin (ANG) were inhibited transfected with miR-6747-5p mimics. Further studies showed that the overexpression vectors of EGFL6 transfected into ESCC cells could reverse the inhibitory effects induced by miR-6747-5p. These findings reveal that miR-6747-5p could target EGFL6 and inhibit tumor angiogenesis and ESCC progression. miR-6747-5p may be a promising biomarker for the anti-angiogenic treatment of ESCC.

Open Access

Article

Research on the application of sports biomechanics in optimizing the effect of physical training

Xiaofeng Gou, Wei Xiong

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1133 , 2025, DOI: 10.62617/mcb1133

Abstract：

This paper discusses the application of sports biomechanics in optimizing the effect of sports training, finds out the existing problems through quantitative evaluation of athletes’ technical movements, and puts forward improvement suggestions to maximize the training effect. In this study, 12 professional long jumpers were taken as the object, and advanced equipment such as high-speed photography, computer analysis and photoelectric timer were used to record the long jump movements of athletes in all directions, and the biomechanical parameters were analyzed. The results show that after four weeks of personalized training, the key performance indexes of athletes such as take-off speed, horizontal displacement, vertical jump height, landing technique and muscle strength have been significantly improved, and the average long jump performance has been significantly improved. Principal component analysis (PCA) reveals the key biomechanical factors that affect the performance of long jump, including take-off speed, horizontal displacement and vertical jump height. In addition, hierarchical cluster analysis helps to identify the technical characteristics and training needs of different athletes, which provides a basis for making personalized training plans. The results show that the application of sports biomechanics not only improves athletes’ performance, but also helps to reduce sports injuries and prolong sports life, and provides scientific training guidance for coaches. This study has important theoretical and practical value for promoting the development of sports science and improving the level of competitive sports.

Open Access

Article

Biomechanical and biodegradation performance of CSA-CSF reinforced cementitious composites: A bio-inspired approach

Bo Peng, Haoyu Li , Yan Xu, Hanyu Li

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1317 , 2025, DOI: 10.62617/mcb1317

Abstract：

This study investigates the mechanical, biodegradation, and microstructural performance of cementitious composites reinforced with Corn Straw Ash (CSA) and Corn Straw Fiber (CSF) for applications in bio-inspired materials and sustainable engineering. CSA, a pozzolanic material, enhances matrix densification, while CSF provides crack-bridging and toughness improvement. Dynamic mechanical testing under cyclic loading demonstrated that CSA-CSF composites exhibit superior fatigue resistance, retaining 85% of their initial compressive strength after 1000 cycles. Biodegradation studies in simulated body fluid (SBF) and acidic environments revealed that the composites maintain 75% compressive strength in SBF over 28 days, highlighting their potential for bioactive scaffolds. Scanning electron microscopy (SEM) and quantitative porosity analysis showed that CSA-derived Calcium Silicate Hydrate (C-S-H) gel effectively filled voids, while CSF enhanced fiber-matrix bonding, mimicking the hierarchical structure of biological systems. The results emphasize the dual benefits of CSA-CSF composites in dynamic environments and their alignment with sustainable and bio-inspired design principles. This research provides insights into the development of materials for biomechanical applications, including tissue engineering scaffolds and earthquake-resistant structures.

Open Access

Article

The impact of fatigue on the jumping mechanics and injury risk of basketball players

Tianci Zhao

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1026 , 2025, DOI: 10.62617/mcb1026

Abstract：

Fatigue can significantly alter an athlete’s biomechanics and performance, which can increase their risk of injury. Important basketball moves like jump shots (JS) and countermovement jumps (CMJ) primarily use the muscles in the lower back and lower limbs. Basketball players’ jumping mechanics, performance, and risk of injury during CMJ, JS, and ankle sprains were all examined. A total of 415 male collegiate basketball players participated in the league, this season representing varying levels of jumping mechanics. Surface electromyography, a force plate, and a 3D motion analysis system were used to gather data. Field-goal percentage, the center of mass’s (CM) lowest point, joint angles during takeoff and landing, and Electromyography data from the lower leg muscles, erector spinae limbal, and rectus femoris were among the parameters that were recorded. Lower back muscle tiredness was created, and performance was evaluated after the fatigue. Data was analyzed using SPSS, with paired-sample t -tests, logistic, and Multiple Regression tests employed to examine the impact of fatigue on performance and injury risk. These tests assessed how fatigue affects shooting accuracy and joint angles, and increases the chance of injuries in basketball players. Following a period of tiredness, athletes’ field-goal percentages significantly decreased, whereas their CM lowest point increased on jump shots. In both CMJ and JS, fatigue leads to reduced knee flexion angles and increased ankle plantar flexion during landing, changing the contribution ratio of both legs. Due to impaired mechanics, these biomechanical changes suggest an increased probability of ankle sprains and an elevated risk of damage, especially during landing. The risk of lower back, knee, and ankle injuries increased due to major athletic impairments and altered landing mechanics caused by lower back muscular fatigue. To reduce basketball players’ risk of injury, these data highlight how crucial it is to address fatigue in training and recovery plans.

Open Access

Article

Biometric recognition and analysis of sports teaching behavior based on wearable devices

Hui Ma, Xuelian Ma

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1245 , 2025, DOI: 10.62617/mcb1245

Abstract：

This study introduces a lightweight, multi-node IMU-based motion capture system optimized for biomechanical analysis, addressing limitations of traditional optical systems and challenges in sensor drift and noise. Multi-node IMU systems offer distinct advantages in biomechanical analysis, such as portability, affordability, and the ability to capture motion data in real-world environments, making them particularly suited for applications in gait analysis, sports performance, and rehabilitation. Enhanced calibration techniques correct biases in accelerometers, gyroscopes, and magnetometers, while an optimized Madgwick algorithm ensures accurate, real-time motion tracking. The system’s scalable design, supported by high-throughput USB 3.0 communication, enables precise capture of human motion. Experimental validation confirms the system’s affordability, robustness, and suitability for biomechanics, offering a practical and effective tool for advancing human movement research.

Open Access

Article

Biosensing technology based on biomechanics in psycho analysis: Improving the efficiency of ideological and political education

Donghong Lei, Yi Pi

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 601 , 2025, DOI: 10.62617/mcb601

Abstract：

In recent years, advancements in technology have significantly transformed educational paradigms, particularly through the integration of biomechanics in teaching methodologies. The incorporation of biomechanical analysis in educational settings provides valuable insights into students' physical engagement and motor skills development. This study aims to leverage biomechanical data to enhance the effectiveness of physical education and sports training. Biomechanical sensors, such as motion capture systems and wearable devices, collect critical data on parameters like gait, balance, and muscle activity. By analyzing this data, educators can gain a deeper understanding of students' physical performance and identify areas for improvement. We propose a novel biomechanical optimization framework utilizing a multi-kernel support vector machine (MK-SVM) to assess students' physical strain levels during activities. In the preprocessing stage, a median filter is employed to eliminate noise from the motion data. Features are extracted using power spectral density (PSD) analysis to evaluate students' physical responses during instructional activities. The proposed method utilizes algorithms to create personalized training environments, identifying physical responses and facilitating real-time feedback for enhanced engagement in sports and physical education. The MK-SVM algorithm is applied for feature selection, effectively categorizing student strain levels to refine personalized learning strategies. Results indicate that our approach outperforms traditional methods, achieving high accuracy (92%), Recall (98%), precision (80%), and F1-Score (88%) in assessing students' physical strain.   This study demonstrates how biomechanics and technology can revolutionize physical education, fostering more adaptive and responsive learning environments.

Open Access

Article

The biomechanical influence of Qianlong health maintenance movement on the mental health of the elderly people

Li-Jun Wang, Jing-Gang Li

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 760 , 2025, DOI: 10.62617/mcb760

Abstract：

Purpose: As mental health issues among the aging population become increasingly prevalent, effective interventions that incorporate physical movement are essential. To explore the influence of Qianlong health exercise on the mental health of the elderly people, emphasizing the biomechanical aspects of physical activity. Methods: A general situation questionnaire and the SCL-90 were used to measure the psychological status of 627 elderly people. Results: There were significant differences in the dimensions of somatization, obsessive symptoms, interpersonal sensitivity, depression, anxiety, hostility, terror, paranoia, psychosis, sleep diet and total score, especially in the dimensions of interpersonal sensitivity, depression, anxiety, paranoia and psychosis. Furthermore, the study identified significant variations in the length, frequency, and forms of Qianlong health exercise practiced by participants, indicating that these factors may play a critical role in influencing mental health outcomes. The biomechanical properties of Qianlong health exercise, characterized by controlled movements that enhance balance, coordination, and flexibility, may contribute to improved psychological well-being by reducing stress and promoting relaxation. Conclusion: Qianlong health exercise represents an effective intervention for enhancing mental health among the elderly, integrating physical activity with psychological benefits. Future research should focus on the specific biomechanical mechanisms that mediate these effects and explore how such exercises can be incorporated into comprehensive health promotion strategies for the aging population. This approach not only addresses physical fitness but also fosters mental resilience, making it a valuable addition to geriatric health programs.

Open Access

Article

Kinetic elements and brushstroke dynamics in painting through the lens of biomechanics

Zhenpeng Zhao

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 763 , 2025, DOI: 10.62617/mcb763

Abstract：

This study explores the biomechanics of brushstroke dynamics in painting, focusing on the physical demands of different brushstroke types and their underlying kinetic elements. Through an experimental method combining motion capture, force sensors, and electromyography, we analyzed the joint angles, Muscle Activation (MA) patterns, and force application across four brushstroke types: broad strokes, fine detail, stippling, and circular motions. Key findings revealed that broad strokes required the most extensive range of motion, with shoulder and elbow joint angles averaging 45°–60° and 30°–40°, respectively, reflecting the involvement of larger muscle groups in creating expansive movements. Fine detail strokes, in contrast, relied predominantly on wrist flexion and extension (15°–20°), necessitating greater precision and stability from distal muscles. Force analysis showed that stippling generated the highest mean force (10.2 N) due to repetitive dabbing motions, whereas fine detail strokes exhibited minimal force variability, indicating controlled, delicate muscle engagement. Electromyography data indicated peak MA in the extensor carpi radialis and flexor carpi radialis during fine and circular strokes, highlighting the unique demands of rotational and fine motor control in painting. These findings underscore the complex interplay of movement, force, and MA required for different painting techniques, contributing valuable insights for optimizing technique and preventing repetitive strain in artists. This research provides a foundational biomechanical understanding of brushstroke execution, with implications for art education, rehabilitation, and ergonomic interventions in the arts.

Open Access

Article

The diagnostic value of carotid ultrasound in stroke prevention: Cellular molecular biomechanics-anchored exploration of current applications and future trails

Min Zhang, Rong Liu

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1013 , 2025, DOI: 10.62617/mcb1013

Abstract：

Stroke continues to be a major public health concern involving high morbidity and mortality in most parts of the world with far reaching economic impact. About two thirds of these cases are caused by ischemic strokes that are linked to carotid artery disease. Identifying high-risk stroke patients is crucial for initiating appropriate management. At the cellular molecular biomechanics level, the carotid artery’s endothelial cells experience shear stress. Changes in blood flow patterns can disrupt the mechanotransduction pathways within these cells. Ideally, high risk stroke patients should first be identified for proper management to be begins. Carotid artery disease or carotid stenosis and plaque formation is one of the major and modifiable risk factors for ischemic stroke, thereby the importance of accurate diagnostic assessment cannot be overstressed. The current uses, accuracy, and future developments of carotid ultrasound as a diagnostic tool for stroke prevention are discussed in this paper. Carotid ultrasound that is noninvasive and relatively inexpensive is a central tool in evaluating the degree of stenosis and plaque features that are vital in risk of stroke. It can detect alterations in the intima-media thickness, which reflects changes in the cellular and extracellular matrix composition of the artery wall. The biomechanical properties of plaques, such as their stiffness and vulnerability, can also be inferred. In the review, difficulties in stroke risk detection and features of carotid ultrasound that were outlined include its effectiveness in identifying stroke risk, in comparison with other imaging techniques, the incorporation of carotid ultrasound into clinical practice for early strokes detection. New developments such as carotid elastography and imaging with the help of artificial intelligence algorithms are also presented to exemplify the increasing possibilities of enhancing diagnostic accuracy. The primary value of carotid ultrasound is in stroke prevention because it offers a preliminary and precise means of diagnosing carotid artery disease. However, further studies are needed to explore additional applications, enhance diagnostic precision, and develop more effective preventive healthcare strategies, taking into account the cellular molecular biomechanics of the carotid artery and its associated pathologies.

Open Access

Article

Enhancing college students physical education using artificial intelligence-optimized teaching system based on biomechanics

Zixuan Gao, Hongjing Guan, Zhi Tan

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 503 , 2025, DOI: 10.62617/mcb503

Abstract：

Physical Education Teaching concerns the process of leading students to perform different tasks, games, and workouts that improve physical fitness, body control, and health. In the realm of cell and molecular biomechanics, physical education teaching can be regarded as a means to induce specific physiological responses at the microscopic level. The various physical activities in which students partake, like diverse tasks and workouts, exert mechanical forces that permeate throughout the body and impinge upon cells and tissues. During physical exertion, cells within muscles, bones, and connective tissues are subject to biomechanical stress. This stress triggers a cascade of molecular events. Teachers focus on enhancing spatial and manual skills, promoting cooperation, and setting up priorities. In this research, it is proposed to learn about the teaching system of physical education in colleges and universities using artificial intelligence (AI) optimization algorithm. Thus, for predicting the achievements of college students in physical education, we propose the Blue Monkey optimization-driven Weight-Tuned AdaBoost (BM-WTAdaBoost) algorithm. The observations and variables were derived from typical physical education programs of college students during their training sessions. A data pre-processing technique known as min–max normalization is applied to the obtained raw data to enhance its quality. For nonlinear data, Kernel Principal Component Analysis (kernel-PCA) is employed as it helps in extracting the nonlinear information, which in turn helps in making accurate predictions. The following is our proposed model: BM opt with WTAdaBoost to improve selecting features and model accuracy in predicting college students’ physical education outcomes. Python program uses our suggested technique. The finding assessment phase assesses the suggested model’s prediction efficacy using several measures, including the accuracy ratio (99.8%), F1-score (95.56%), prediction ratio (98.24%), interaction ratio (97.2%), efficiency ratio (98.24%), performance ratio (97.2%), and error rate (5.62%). We also performed a comparative analysis with different traditional approaches to assess the efficacy of the suggested strategy. Comparative analysis with traditional methods shows the superiority of this approach in predicting physical education outcomes considering cell and molecular biomechanics, providing a novel perspective for understanding and optimizing physical education in relation to the microscopic biological world.

Open Access

Article

Research on biomechanics-informed rural planning strategies for enhancing biodiversity and health

Xiuli Yang, Miaomiao Han

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 626 , 2025, DOI: 10.62617/mcb626

Abstract：

Rapid urbanization has resulted in decreased biodiversity, adversely impacting ecosystem functions and human health, especially in rural regions. Biomechanics-informed rural planning integrates principles of biological mechanics with biodiversity enhancement and public health objectives to establish sustainable communities. Purpose: This study aims to foster resilient ecosystems and healthier rural populations by introducing biomechanics-informed approaches to rural planning that synergize biodiversity enhancement with health promotion. Methods: This study bridges the knowledge gap by examining the relationship among biomechanically efficient behaviors, personal health, and ecosystem-based disaster risk reduction (EDRR) through the lens of the Health Belief Model (HBM). Structural equation modeling (SEM) was employed to investigate the correlations between the study's key variables. The research focused on a rural community impacted by disaster to test the hypotheses, exploring biomechanics-informed rural planning strategies that facilitate sustainable development and biodiversity enhancement. Results: The findings indicate that health perceptions and EDRR attributes indirectly influence biomechanically efficient behaviors. Specifically, participation in activities that support biodiversity is positively associated with perceptions of social integration benefits, EDRR awareness, and health promotion. Conclusion: This study underscores the potential to integrate biomechanics into Emergency Disaster Risk Reduction (EDRR) initiatives and community planning to encourage healthy lifestyles and enhance the environmental sustainability of resilient communities.

Open Access

Article

The integration of biomechanics and the application of green materials in the construction of sports facilities under environmental sustainability

Xian Liu, Xiangping Mei, Jianqiang Guo

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2) , 2025, DOI: 10.62617/mcb696

Abstract：

With the in-depth implementation of the Scientific Outlook on Development, in order to implement the national basic energy-saving policies and various emission reduction mechanisms, as well as the demonstration and promotion role of universities in energy conservation and emission reduction, the state has put forward the idea of further supporting the construction of energy-saving campuses in higher education and universities. This paper delves into the application of green and environmentally friendly materials in the construction of sports facilities, not only from the perspective of ecological sustainable development but also in close connection with the field of biomechanics. Biomechanics plays a crucial role in the design and use of sports facilities. When applying green materials, it is essential to consider how these materials interact with the human body's mechanics during sports activities. For example, different sports demand specific mechanical properties from the facilities, such as the right amount of elasticity, friction, and shock absorption. Green materials, when selected and designed with biomechanics in mind, can enhance the performance and safety of athletes while maintaining environmental friendliness. To assess the feasibility of green materials in this context, this paper presents an evaluation method that integrates the Analytic Hierarchy Process (AHP) and information entropy. This approach incorporates biomechanical factors into the index system. By doing so, the combined weight value of each component in the system can more accurately reflect the real-world situation. Compared to traditional evaluation methods, this integrated approach effectively mitigates the subjectivity in determining weight coefficients. It also ensures that the significance of each evaluation index, especially those related to biomechanical performance, is fully considered. The experimental results in this paper show that the use of AHP to evaluate the advantages of green environmental protection materials, the average weight reaches 0.8275. This finding strongly suggests that the application of green materials in sports facilities construction is highly viable. These materials not only contribute to environmental protection but also offer biomechanical advantages, ensuring the long - term sustainability and functionality of the facilities for athletes.

Open Access

Article

Biomechanical research on the construction and optimization of youth basketball training system based on the integration of sports and education

Zechun Hu, Zhengfeng Huang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 797 , 2025, DOI: 10.62617/mcb797

Abstract：

The development and improvement of a youth basketball training program founded on the fusion of education and sports is investigated in this study. Athlete performance and academic advancement must be balanced in light of the growing need for comprehensive youth development. Biomechanical factors play a significant role in both sports performance and injury prevention, making it essential to integrate them into the training program design. To increase the effectiveness and design of training programs, the suggested model makes use of the Tabu Search Optimized Intelligent Random Forest (TSO-IRF) algorithm. The TSO-IRF identifies important physical, technical, and cognitive elements affecting basketball play by combining search-based optimization with machine learning (ML) approaches from a biomechanical perspective. It focuses on elements such as joint forces, muscle activation patterns, and movement kinematics, which are fundamental in determining an athlete's performance and injury risk. The research gathers information on youth basketball training programs, with a specific emphasis on biomechanical aspects. This includes information on players' body mechanics during different basketball movements, like jumps, shots, and passes. By integrating this data, the study ensures that the goals of educational development and sports training are aligned, while also considering the biomechanical requirements of the athletes. TSO-IRF is used to evaluate these multidimensional features and provides individualized training suggestions in line with the performance and educational objectives of both sports. Experimental results indicate that the TSO-ERF model can perform better than traditional methods, providing higher prediction recall (94.26%), accuracy (97.81%) and precision (97.21%) in development metrics for players. Additionally, the model shows improved adaptability across various skill levels as it can adjust training recommendations based on an athlete's unique biomechanical characteristics. The proposed youth basketball training system optimizes loads in training, reduces risks of injury, and develops young athletes over the long term. It facilitates athletic success but fosters cognitive and emotional development so that the fields of sport and education may converge. Future work involves the application of this model in other sports disciplines and algorithm refinement to take care of larger datasets that would help deliver real-time performance feedback.

Open Access

Article

Optimization of alpine skiing turning techniques based on biomechanics

Changfeng Li, Jiandong Wang, Bing Zhou, Baoku Sui

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 999 , 2025, DOI: 10.62617/mcb999

Abstract：

Alpine skiing turning technique requires high coordination of movements, but the existing training methods lack in-depth analysis of biomechanical characteristics. Athletes are prone to injuries during training. Technical optimization mainly relies on summarizing experience and lacks a precise quantitative basis. This paper aims to systematically analyze and optimize alpine skiing turning techniques from a biomechanical perspective, build a scientific action model and data analysis system, realize quantitative evaluation of technical movements, improve training safety and technical level, and provide scientific guidance for athletes. The study uses motion capture equipment to record three-dimensional motion trajectories and pressure sensors to collect mechanical data. By building an analysis model based on biomechanics, key features such as joint angles and torque changes are extracted, and an optimization scheme is designed in combination with a nonlinear multi-objective optimization algorithm. Based on these models and algorithms, a real-time feedback system is developed to provide personalized training suggestions to support athletes in adjusting movements and improving their technical level. The experimental results show that compared with the traditional training method, the coordination and balance of the optimized training model are improved by about 23.6% and 13.6% respectively, the action efficiency is improved by about 26.9%, and the risk of injury is reduced by more than 20%. In addition, the results of the model generalization ability test also show that the optimized training method has the characteristics of adapting to different groups. This shows that the optimized training method can significantly improve movement coordination and efficiency while reducing the risk of sports injuries, providing a new path for the scientific training of alpine skiing.

Open Access

Article

Study on dexterous structure and control of bio-inspired musculoskeletal robots in artificial intelligence environment

Qiyuan Wang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 689 , 2025, DOI: 10.62617/mcb689

Abstract：

The design and development process of bio-inspired musculoskeletal robots in the artificial intelligence environment integrates mechanical design, control algorithms, real-time computing, variable sensing, and other fields of technology, which can provide effective mechanical support for the user’s actions in the process of use, and has a broader application prospect in a number of fields. In the process of exoskeleton robots moving from experimental research and development to practical applications, the comfort of the use process is an important evaluation criterion. Therefore, from the perspective of user comfort, this paper takes the waist exoskeleton robot as the research object, and conducts a design study on the structure and control of the exoskeleton robot.

Open Access

Article

Application of virtual reality in e-commerce: Taking the experience of trying on sports equipment as an example

Lin Gan

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 997 , 2025, DOI: 10.62617/mcb997

Abstract：

Traditional e-commerce platforms have the problem that users cannot try on sports equipment in person, and it is difficult for consumers to perceive its size, comfort and dynamic performance before purchasing. This limitation leads to high return rates and difficult purchasing decisions. This paper introduces a virtual try-on solution with higher accuracy and more immersion. After using 3D scanning technology to obtain the user’s body data and combining it with SMPL (Skinned Multi-Person Linear Model) to generate the user’s body model, a posture optimization algorithm is used to adjust the dynamic posture of the user model and the PoseNet optimization model is used to adapt it to the user’s dynamic motion scenes. Next, Unity Physics is used to achieve the dynamic performance of sports equipment materials, high-definition texture mapping technology is used to reproduce the visual effects of equipment materials to ensure that the appearance is consistent with reality, and sports scenes are constructed to simulate the actual performance of equipment in different environments. Users can use motion capture devices to simulate running, jumping and other movements to feel the suitability of sports equipment. Then, based on the user’s body shape data and sports scene preferences, Deep Q-Learning is used to recommend sports equipment options suitable for the user. Finally, the system adjusts the virtual try-on experience in real time, showing a variety of combination effects, helping users quickly find their favorite products. Experiments show that the performance error between virtual equipment and real equipment is only 1.35%, the virtual try-on pass rate exceeds 90%, and the return rate is less than 10%, which verifies the feasibility of virtual reality technology in e-commerce and improves users’ online shopping experience.

Open Access

Article

New paths to promote athletic injury prevention by integrating statistics and sports biomechanics

Yiming Zhao

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1000 , 2025, DOI: 10.62617/mcb1000

Abstract：

Athletic injuries are a common problem in sports. Due to the insufficient processing of multimodal biomechanical data by traditional prevention strategies, personalized risk prediction cannot be achieved. To this end, this paper adopts an athletic injury prevention method based on sparse principal component analysis (SPCA) and spatio-temporal graph convolutional network (ST-GCN). The Vicon Vantage V5 3D motion capture system and the Noraxon Ultium EMG electromyography acquisition device are used to obtain the athlete’s joint angle change rate, ground reaction force (GRF) and electromyographic activity data, and the SPCA method is used to extract key biomechanical features, thereby reducing data redundancy and improving the representativeness of features. Subsequently, ST-GCN is used to construct a dynamic risk prediction model to capture the temporal changes and spatial dependencies in the motion sequence to achieve precise and efficient risk assessment. In the experimental verification, the prediction accuracy of the model reaches 95.3% when the number of features was 20, and the ability to provide risk feedback in real-time is realized to generate personalized injury prevention strategies. Studies have shown that the integration of statistics and sports biomechanics has effectively improved the efficiency of athletic injury prevention and provided new ideas for scientific and precise sports management.

Open Access

Article

A study on the application of machine learning algorithms incorporating biomechanical principles in optimising the health status assessment of electric vehicle power batteries

Jiyuan Zhang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 722 , 2025, DOI: 10.62617/mcb722

Abstract：

This study addresses the problem of power battery health state assessment for electric vehicles, integrating biomechanical principles and machine learning algorithms to investigate the health state assessment accuracy of different types of power batteries under different working conditions. The study adopts a variety of data-driven methods to deeply analyse the performance degradation law of power batteries. The results show that the machine learning algorithm incorporating biomechanical principles can effectively improve the accuracy of power battery health state assessment, especially under complex working conditions, and exhibits better robustness. The current status of power battery health state assessment technology is reported, and it provides a useful reference for future power battery health management in electric vehicles.

Open Access

Article

Algorithms for digital cultural tourism ecological model with biomechanical considerations in VR scene interactions

Jing Peng

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 745 , 2025, DOI: 10.62617/mcb745

Abstract：

Digital cultural tourism is an emerging form of tourism that presents cultural heritage and tourism resources digitally to users, providing immersive travel experiences. However, traditional methods of constructing virtual scenes often rely on manual modeling, leading to low efficiency and high costs. The existing digital cultural tourism platforms mostly provide static and pre-set content, lacking interaction with users, making it difficult to achieve personalized recommendations and interactive experiences. In response to these issues, this article is based on VR (Virtual Reality) scene intelligent generation and interactive algorithms, and aims to optimize the overall synergy between the presentation of cultural resources and user experience by constructing a digital cultural tourism ecological model. Drawing on biomechanical principles, the study emphasizes the importance of natural user interactions and physical engagement in enhancing the immersive experience. Firstly, the Lindenmayer system (L-system) and parameterized generation rules are used to generate complex natural landscapes and architectural structures. Natural and textured scene details are added using the Perlin noise algorithm. Using GANs (Generative Adversarial Networks) technology, generative and discriminative networks are trained to generate more realistic VR scenes, further enhancing the realism and detail representation of the scenes. At the same time, a gesture recognition technology combining CNN (Convolutional Neural Network) and LSTM (Long Short-Term Memory) models, along with a speech recognition algorithm based on DNN (Deep Neural Networks), is adopted to enhance the natural interaction between users and virtual scenes. By combining collaborative filtering algorithms with user behavior data, personalized content recommendations are realized, enhancing user engagement and satisfaction. The efficiency test of scene modeling, the total time required to generate scenes using the model in this article is only 84 hours, which is much lower than manual modeling. In the interactive test, the highest success rate of the model in this article in gesture recognition reaches 94%. The experimental results have verified the advantages of the model in this article in improving scene modeling efficiency and enhancing immersive experiences through biomechanically informed interactions.

Open Access

Article

Applications and challenges of artificial intelligence-driven 3D vision in biomedical engineering: A biomechanics perspective

Lei Wang, Zunjie Zhu

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1006 , 2025, DOI: 10.62617/mcb1006

Abstract：

This paper explores the applications and challenges of artificial intelligence (AI)-driven 3D vision technology in biomedical engineering, with a specific focus on its integration with biomechanics. 3D vision technology offers richer spatial information compared to traditional 2D imaging and is increasingly applied in fields like medical image analysis, surgical navigation, lesion detection, and biomechanics. In biomechanics, AI-driven 3D vision is used for analyzing human movement, modeling musculoskeletal systems, and assessing joint biomechanics. However, challenges persist, including image quality, computational resource demands, data privacy, and algorithmic bias. This paper reviews the development of 3D vision technology and AI, discusses its applications in biomedicine and biomechanics, and addresses the key technical obstacles, offering insights into the future development of these technologies in the context of biomedical and biomechanical research.

Open Access

Article

A biomechanics-oriented study on the impact of AIGC on user interaction and ergonomics in visual communication design

Yiwen Chen

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 766 , 2025, DOI: 10.62617/mcb766

Abstract：

This study investigates the biomechanical implications and ergonomic impacts of AI-generated content (AIGC) integration in visual communication design workflows. Through a comprehensive analysis of 23 professional designers in Chengdu, China, we examined the physical stress patterns, user interaction dynamics, and overall ergonomic outcomes when transitioning from traditional to AIGC-assisted design processes. The research employed a mixed-method approach combining quantitative biomechanical measurements with qualitative user experience assessments over 12 weeks. Results revealed significant reductions in muscle activity across key muscle groups, with the upper trapezius showing the most significant decrease (−3.6% MVC, p < 0.001) during AIGC-assisted tasks. This change in muscle activity can be further linked to alterations in the body's postural stability and load distribution, which are core considerations in biomechanics. Movement efficiency metrics, which are inherently related to biomechanical performance, demonstrated a 27.9% reduction in task completion time ( p < 0.001) and a 33.3% decrease in design iterations. Quality assessment scores improved across all dimensions, with Creative Innovation showing the highest enhancement (+1.8 points, p < 0.001). User satisfaction metrics indicated significant improvements, with consistent gains of 1.1 points (on a 5-point scale) across all measured dimensions ( p < 0.001). Notably, the study identified distinct adaptation patterns between novice and experienced users in terms of their biomechanical responses. Experienced users demonstrated significantly faster response times in AIGC prompt input (8.94 ± 1.87 s vs 18.62 ± 3.15 s, p < 0.001), which can be associated with differences in their neuromuscular coordination and motor learning abilities. While AIGC integration initially increased certain types of errors (+51.2% in input errors), it led to substantial reductions in tool misuse (−40.4%) and design revisions (−39.9%). These findings suggest that AIGC integration can significantly reduce physical stress while improving design efficiency and quality outcomes, all of which are intertwined with the biomechanical functioning of the body during the design process. The research provides evidence-based recommendations for optimizing AIGC implementation in professional design workflows, taking into account the biomechanical and ergonomic factors that contribute to the overall well-being and creative productivity. This study has important implications for software development, workplace health policies, and the future direction of AI-assisted creative work, as it highlights the significance of considering biomechanics in the integration of advanced technologies within creative domains.

Open Access

Article

Innovative design and implementation path of biomechanical elements in intelligent landscapes

Delin Zeng

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1277 , 2025, DOI: 10.62617/mcb1277

Abstract：

With the acceleration of urbanization and rapid development of intelligent technologies, incorporating biomechanical elements into intelligent landscape design has become a crucial approach to enhancing urban landscape quality. This research conducts a systematic study on the innovative design and implementation approaches of biomechanical elements in intelligent landscapes, proposing a “Bio-Intelligence-Environment” trinity design principle system and developing new intelligent composite materials and biomimetic multi-level structural design methods. Experimental testing demonstrates that the developed intelligent composite materials achieve a tensile strength of 576 MPa, a 32.5% improvement over traditional materials, with intelligent response sensitivity increased by 45.3%. Through biomimetic multi-level structural design, component weight is reduced by 18.5% while bearing capacity increases by 22.3%, achieving a static load capacity of 2850 N/m 2 . The intelligent control system reaches a recognition accuracy of 98.7%, an improvement of 15.4 percentage points over traditional systems, with control precision reaching ± 0.08 mm. Environmental adaptability tests show that the system maintains stable operation within a temperature range of −25 ℃ to 65 ℃, with performance degradation not exceeding 5.8%, and relative humidity adaptation ranging from 20% to 95%. Field application data indicates a system stability rate of 99.3%, with an average fault-free operation time of 8500 h and annual operation and maintenance costs accounting for 3.2% of initial investment, a 45% reduction compared to traditional systems. User experience evaluation shows an overall satisfaction score of 92.3, with intelligent interaction satisfaction reaching 95.2%. Economic benefit analysis reveals that mass production reduces single system cost to 325,000 yuan, with a 2.8-year investment recovery period and an internal rate of return of 24.5%.

Open Access

Article

Research on the structural design of exoskeleton assisted transport robot combined with reinforcement learning algorithm under the background of artificial intelligence

Zhongnan Liu

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1014 , 2025, DOI: 10.62617/mcb1014

Abstract：

With the comprehensive interface between “Made in China 2025” and Industry 4.0, the handling mode of the handling system is constantly updated and developed, and a new type of handling mode, which is assisted by exoskeleton and other equipments to complete the handling work of workers, has been gradually applied. However, most of the existing exoskeleton-assisted robots are expensive and complicated in structure, which are not applicable to the actual needs of ordinary workers. Therefore, it is of great significance to design an exoskeleton-assisted handling robot that is applicable to the needs of ordinary workers. Based on this, this paper designs a relatively simple structure and low cost exoskeleton-assisted handling robot, and introduces the BN-Q-learning algorithm to give the control strategy of the robot, and finally simulates and analyzes the reliability of the handling robot, and the results show that the exoskeleton-assisted handling robot designed in this paper has a high reliability, and the force situation and the human body’s joints are relatively well matched when handling heavy objects. The results show that the exoskeleton assisted handling robot designed in this paper is highly reliable, and the force situation when handling heavy objects matches the human body joints.

Open Access

Article

Analyzing biomechanical force characteristics in sports performance monitoring using biochemical sensors and internet of things devices

Jing Liang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 727 , 2025, DOI: 10.62617/mcb727

Abstract：

This study explores the application of Internet of Things (IoT) devices and biochemical sensors in sports performance monitoring, focusing on the biomechanical force characteristics of athletes to address limitations in traditional methods, such as limited data types, poor real-time accuracy, and insufficient visualization. Emphasizing mechanobiological principles, the analysis targets key force-producing regions of the body—such as the feet, legs, and torso—to optimize energy efficiency, motion precision, and overall athletic performance. Biochemical sensors were employed to monitor real-time biomechanical and physiological data, while IoT devices ensured accurate data transmission, visualization, and feedback. Data accuracy was enhanced through methods such as zero correction, timestamp synchronization, and Kalman filtering, while data transmission efficiency was optimized using a lossless compression algorithm, hierarchical structuring, the MQTT protocol, and encryption via the AES algorithm. Data organization utilized a star-structured MySQL database with composite indexing for swift access. Analytical tools such as the Apriori algorithm for data correlation, linear discriminant analysis for feature extraction, and multi-source data fusion enabled detailed visualization of performance metrics. Experimental applications in football and sprinting demonstrated the effectiveness of IoT-based monitoring. Football experiments captured multi-dimensional data on technical characteristics, while sprint tests recorded precise performance metrics, including real-time speed profiling and timing accuracy. For instance, in a 100-meter sprint test, an IoT system measured an athlete's performance at 12.54 seconds with 100% accuracy, surpassing manual timing methods. These findings highlight the transformative potential of IoT devices and biochemical sensors in sports analytics, offering enhanced accuracy, real-time tracking, and actionable insights to refine athletic performance and decision-making.

Open Access

Article

The relationship between the quality of sports facilities and people’s satisfaction with exercise—The chain mediating effect of active participation and self-efficacy in the context of biomechanics

Liping Wang, Ping Wang, Sixuan Sun, Yiling Fan

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 789 , 2025, DOI: 10.62617/mcb789

Abstract：

In order to explore the relationship between active participation and self-efficacy in the quality of sports facilities and exercise satisfaction, this study takes into account the perspective of biomechanics. A survey was conducted among 361 urban residents aged 16 and above in Yongzhou City. The “Sports Facilities Quality Scale”, “Active Participation Scale”, “Self-Efficacy Scale”, and “Exercise Satisfaction Scale” were utilized, with an added consideration of biomechanical factors. Biomechanics, which examines the mechanical aspects of human movement during exercise, provides a crucial framework for understanding how sports facilities interact with the human body. High - quality sports facilities, designed in accordance with biomechanical principles, can significantly influence the physical experience of exercise. For example, the surface material and structure of a running track can affect the impact forces on joints during running, and the ergonomic design of fitness equipment can enhance the efficiency and comfort of movements. These biomechanical factors directly impact a person’s active participation in exercise. When facilities are biomechanically optimized, individuals are more likely to engage actively in physical activities, as they experience less discomfort and reduced risk of injury. The results showed that: 1) The quality of sports facilities, active participation, self-efficacy and exercise satisfaction were significantly correlated with each other. 2) Active participation played a single intermediary role between the quality of sports facilities and exercise satisfaction, accounting for 26.81% of the total effect, and self-efficacy played a single intermediary role between the quality of sports facilities and exercise satisfaction; Active participation and self-efficacy play a chain intermediary role between the quality of sports facilities and exercise satisfaction, accounting for 26.34% of the total effect. Conclusion: Considering biomechanics, the quality of sports facilities indirectly affects the exercise satisfaction of urban residents in Yongzhou City through the chain mediation of active participation and self - efficacy. In the context of national fitness, high - quality sports facilities, designed with biomechanical principles in mind, play a positive and crucial role in promoting residents’ physical exercise, as they can enhance the overall exercise experience from a biomechanical perspective.

Open Access

Article

Effects of low-level laser therapy (LLLT) on skeletal muscle fatigue and damage

Qingkun Feng, Guihua Huang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 919 , 2025, DOI: 10.62617/mcb919

Abstract：

The present study aimed to evaluate the effects of low-level laser therapy (LLLT) on exercise performance and skeletal muscle damage. A randomized, double-blind, placebo-controlled study involved 24 male college swimming athletes. LLLT was administered prior to exercise using a He-Ne laser at 632.8 nm, with a power output of 5 mW, a total irradiation duration of 300 s, and an energy density of 0.3 J/cm 2 per diode or placebo, applied to two points on the rectus femoris muscles bilaterally. The performance in a 200-m breaststroke swim, as well as thigh and leg girth, blood lactate levels, creatine kinase (CK), and lactate dehydrogenase (LDH) levels were assessed before and immediately after the swimming protocol. The LLLT group demonstrated a significant improvement in 200-m breaststroke performance ( p < 0.05) and a significant reduction in thigh circumference, blood lactate, CK, and LDH levels ( p < 0.05) when compared to the placebo group. Pre-exercise photobiomodulation by LLLT improved the 200-m breaststroke swimming performance, and reduced muscle fatigue and damage.

Open Access

Article

Research on the mechanism of promoting precise poverty alleviation through educational informatization based on biomechanical mechanism

Heng Jiang, Guangluan Yin

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1053 , 2025, DOI: 10.62617/mcb1053

Abstract：

Drawing on the theory of biomechanics, this study explores the mechanism of promoting precision poverty alleviation through education informatization. Precision poverty alleviation is at the core of China’s poverty reduction strategy, addressing the root causes of poverty through targeted interventions. Under this framework, education informatization has become a key tool for bridging systemic inequalities by enhancing the quality and equity of education through information technology. From basic digital construction to the deep integration of big data, cloud computing and artificial intelligence, education informatization has made remarkable progress. Analogous to how biomechanical systems optimize force transmission and movement efficiency, it showcases great potential for the optimal distribution of educational resources, enhancing access to education in impoverished regions, and fueling long-term socio-economic progress. However, its role in rural and underdeveloped areas still faces many challenges. Viewing education informatization as a dynamic “biomechanical structure” and borrowing concepts like structural adaptation, load optimization, and connectivity from biomechanics, we posit that big data technology, acting as a “biomechanical signal”, can precisely pinpoint needy students and allocate educational resources adeptly, much like how forces are coordinated in a mechanical system. Based on the fuzzy breakpoint regression model and fixed-effects analysis of CFPS (China Family Panel Studies) data, the study finds that education informatization significantly improves the subjective well-being, health care, and employment outcomes of rural families. This study highlights the innovative role of education informatization in enhancing resilience, equity, and resource efficiency through the synergy of technological evolution and policy adaptation, providing a new perspective on precision poverty alleviation.

Open Access

Article

Exploration of the clinical significance of rapid intraoperative measurement of lymph node thyroglobulin concentration in determining lymph node metastasis of papillary thyroid carcinoma

Shiyi Zhao, Yue Xiang, Wei Yan, Dejie Chen

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1061 , 2025, DOI: 10.62617/mcb1061

Abstract：

Objective: This study aims to evaluate the diagnostic accuracy of thyroid globulin (Tg) detection in elution fluid for intraoperative judgment of lymph node metastasis, and to explore the potential role of biomolecular mechanical behavior in influencing the detection results. By rapidly quantifying Tg levels, the optimal cutoff value was determined, and its potential value in clinical applications was further assessed. Methods: This is a prospective study that included 65 patients with papillary thyroid carcinoma who underwent surgery at Xiangyang Central Hospital's thyroid surgery department from November 2022 to May 2023. A total of 150 cervical lymph node samples were collected. Tg levels were detected intraoperatively using colloidal gold immunochromatographic assay (FNA-TG-GICA), and results were compared with routine paraffin pathology findings. Particular attention was given to the reactivity of Tg molecules in the elution fluid. The optimal cutoff value for Tg test to judge the benign or malignant nature of lymph nodes was determined by plotting the ROC curve and calculating the AUC, to evaluate the diagnostic performance of the intraoperative Tg detection in identifying lymph node metastasis. Results: A total of 150 lymph node samples were included in this study, of which paraffin pathology verification showed 50 metastatic and 100 non-metastatic lymph nodes. The optimal cutoff value for Tg test was 77 ng/mL, with sensitivity of 94.00%, specificity of 96%, and accuracy of 95%. The AUC from the ROC curve analysis was 0.97, indicating high diagnostic accuracy. Further analysis revealed that most of the positive samples were metastatic lymph nodes, and all negative samples were non-metastatic, suggesting that the Tg test performs excellently in determining lymph node metastasis. Conclusion: Elution fluid Tg test demonstrates high accuracy in intraoperatively determining lymph node metastasis. With an optimal cutoff value of 77 ng/mL, it shows excellent sensitivity and specificity. This detection method serves as a rapid and reliable diagnostic tool, providing effective decision support for clinical practice.

Open Access

Article

Application of quantitative analysis of biomechanical data in predicting healthcare investment trends

Zhe Jiao, Shuyu Li

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1156 , 2025, DOI: 10.62617/mcb1156

Abstract：

Traditional methods for predicting investment trends often rely on macroeconomic data, overlooking the influence of individual biomechanical characteristics on decision-making, particularly in the health and medical fields. This paper seeks to enhance the accuracy of healthcare investment trend predictions by integrating high-precision biomechanical data acquisition technology with advanced quantitative analysis methods. High-precision sensors and smart wearable devices are employed to collect individual biomechanical data, encompassing dynamic features such as sports performance, joint angles, and gait. To ensure data quality, a rigorous preprocessing procedure is implemented. Principal component analysis (PCA) is utilized for feature extraction, minimizing redundant information and isolating the most representative biomechanical features. During the data analysis phase, a hybrid model combining random forests and support vector machines (SVM) is employed to predict healthcare investment trends. Random forests are applied for feature selection and regression analysis, while SVMs address classification tasks for trend prediction. The results indicate that the proposed model achieves an accuracy and precision exceeding 0.9, with healthcare investment returns on investment (ROI) ranging from 20% to 50%. The findings underscore the potential of biomechanical data in providing valuable insights for healthcare investment trend predictions, ultimately driving innovation and progress in the industry.

Open Access

Article

Exploring the therapeutic mechanism of the Qing Palace Summer-avoiding Pearl based on network pharmacology and molecular dynamics simulation

Haotian Li, Meixin Zhu, Sile Hu, Yuewei Song, Yanjun Liu, Yuping Zhao

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1329 , 2025, DOI: 10.62617/mcb1329

Abstract：

Heatstroke is a thermal injury disease resulting from excessive water and electrolyte loss, as well as impaired heat dissipation, in hot and humid conditions. Modern medicine typically focuses on physical measures for early heatstroke intervention and prevention, with drug-related research being somewhat limited in scale and scope. In Chinese contexts, heatstroke is often referred to as “Zhongshu”, encompassing symptoms like nausea, vomiting, loss of appetite, emotional fluctuations and agitation, and headaches due to elevated body temperature. Traditional Chinese medicine boasts a long history and extensive literature on treating heatstroke. The Qing Palace Summer-avoiding Pearl, a treasured medicine used by ancient Chinese royalty for “Zhongshu” treatment and prevention, is of particular interest. This study aims to explore a new approach for early heatstroke prevention and intervention using the Qing Palace Summer-avoiding Pearl. We identified the disease types associated with this medicine through disease enrichment analysis and pinpointed the most likely therapeutic targets and effective substances via network pharmacology and molecular docking techniques. Furthermore, we conducted molecular thermodynamic analyses on six target Plant Extracts (PEs) using molecular dynamics simulations, examining parameters such as Root Mean Square Displacement (RMSD), Radius of gyration (Rg), and hydrogen bonds. The results indicated that the complexes exhibited favorable binding performance, which may facilitate further research on the Qing Palace Summer-avoiding Pearl.

Open Access

Article

A multimedia fugacity model for assessing the environmental fate of typical antibiotics in Lake Taihu with emphasis on the biomechanical characteristics of drug delivery systems

Runwu Zhou, Liulin Xi, Ce Wang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 663 , 2025, DOI: 10.62617/mcb663

Abstract：

The extensive use of antibiotics in the Taihu Lake Basin has led to a significant threat to human and environmental health. In this context, the QWASI model is developed to simulate the fate of typical antibiotics in Lake Taihu. Through this model, real-time tracking of the dynamic changes in antibiotic content is possible. The study primarily focuses on evaluating the fate and transfer of antibiotics in the water and sediment phases of the lake. The model results indicate that most of the simulated concentrations and mass fluxes are within the same order of magnitude as the measured values, demonstrating a good simulation effect. However, an underestimation of the simulated output value occurs in some cases. The sediment layer serves as the main accumulation site for antibiotics, and the mass balance equation is a crucial tool for simulating the environmental distribution of antibiotics. Sulfamethoxazole (SMX) exhibits a relatively high concentration in water due to its large model input. The sensitivity analysis reveals that for ATM, SMX, and OFX, the five input parameters with the most significant impact are the half-life in water, sediment-water partition coefficient, sediment solids concentration, sediment particle density, and sediment-water diffusion MTC. For OTC, the impact of lake water depth is more prominent than the sediment-water mass transfer rate. The uncertainty analysis effectively showcases the model’s stability, with the water phase concentration showing better stability. In this process, each factor is assigned a correlation coefficient to represent its influence on the original content. The sediment phase antibiotic concentration has a relatively high uncertainty. The source intensity assessment in this study utilizes direct monitoring data of the Taihu Lake water body, ensuring higher accuracy. The major factor contributing to prediction errors is the ambiguity of the sediment phase, which is affected by numerous environmental factors. Importantly, when considering the fate of antibiotics in the lake, the biomechanical characteristics of potential drug delivery systems play a vital role. The movement and dispersion of antibiotics within the water and sediment are influenced by biomechanical forces. In the sediment, the porosity and permeability, which are related to biomechanical properties, can determine the rate at which antibiotics penetrate and accumulate. Understanding these biomechanical aspects of drug delivery systems can help in devising more effective strategies for antibiotic remediation. It can also provide insights into how the physical environment interacts with the chemical behavior of antibiotics, ultimately contributing to a more comprehensive understanding of the environmental fate of antibiotics in Lake Taihu. This is the first study to explore the fate of antibiotics in Lake Taihu and offers valuable recommendations for the restoration of antibiotic-contaminated lakes. It enriches the research perspectives on water management, especially in relation to addressing water pollution caused by antibiotic abuse.

Open Access

Article

Postural mechanics and artistic control in painting: Investigating the role of movement in artistic creation

Chunlan Shen

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 764 , 2025, DOI: 10.62617/mcb764

Abstract：

Postural mechanics and movement control play fundamental roles in artistic creation, particularly in painting, where precision and fluidity of motion directly influence artistic outcomes. This study investigated the biomechanical relationships between posture, movement, and artistic control in painting practice through a comprehensive analysis of 38 artists (22 Female, 16 Male) ranging from novice to expert-level practitioners in traditional Chinese and contemporary painting techniques. Using an integrated measurement approach combining Motion Capture System (MCS) (Vicon Motion System), electromyography (EMG), and force plate analysis, we examined postural dynamics, movement patterns, and their effects on artistic precision across varied painting conditions. Results revealed significant correlations between postural stability and painting precision ( r = 0.82, p < 0.001), with experienced artists demonstrating superior postural control strategies compared to novices. Analysis of seated versus standing positions showed distinct advantages in stability metrics (88.5 ± 4.2 vs. 82.3 ± 5.6 stability index, p < 0.01), though standing positions offered a more excellent range of motion (58.7 cm ± 7.2 cm vs. 42.3 cm ± 5.6 cm brush reach, p < 0.001). Environmental factors, particularly easel configuration and lighting conditions, significantly impacted performance, with optimal easel height (90%–105% of eye level) correlating with enhanced precision scores (improvement of 18.4 ± 4.2%, p < 0.001). Tool selection analysis demonstrated that medium-length brushes (20 cm–30 cm) provided optimal comfort (8.7 ± 0.9 out of 10) and precision (88.6 ± 3.8 out of 100) scores. Extended painting sessions revealed progressive changes in muscle activation patterns, with expert artists maintaining more consistent movement patterns despite fatigue (8.4 ± 1.2% vs. 18.7 ± 3.2% movement variability, p < 0.001). These findings provide quantitative evidence for the importance of proper postural mechanics in artistic creation and offer practical insights for optimizing painting performance through improved biomechanical awareness and environmental setup.

Open Access

Article

Application of biomechanics in graphic design and ergonomic optimization

Wei Wei

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 984 , 2025, DOI: 10.62617/mcb984

Abstract：

For patients recovering from spinal diseases, ordinary seats often lack support and correction functions, which can easily lead to problems such as spinal curvature and lumbar disc herniation. The study uses MediaPipe to recognize postures and perform 3D graphics modeling, combined with finite element analysis to simulate the coordinated work of the patient’s muscles, bones, and joints, and optimize the design of ergonomic orthosis. First, MediaPipe Pose is used for posture recognition to capture the key point coordinates of the spine and joint positions and obtain dynamic data of the patient’s sitting posture. Next, a 3D model of the patient’s skeleton and spine is built, and the bone structure is generated based on the posture data and refined with ZBrush. Then, a finite element analysis is performed using ANSYS Workbench, and the stress distribution of the spine under the patient’s weight and different sitting pressures is simulated. The orthopedic seat’s geometry and support area distribution are optimized, and adjustment functions are added to improve adaptability. The data results show that the MSE (Mean Square Error) of the optimized spinal curve deviation is only 0.0009; the maximum stress of the intervertebral disc is reduced from 56.1 MPa to 42.4 MPa; the area of the high-stress area is reduced to 12.4cm²; the stress uniformity is improved by 28.1%; the local pressure is reduced by 24.6%. The designed method can significantly reduce the patient’s spinal deviation rate, relieve seat pressure, and have a good rehabilitation auxiliary effect.

Open Access

Article

Development of personalized physical education teaching plan: Research on evaluating students’ physical fitness and sports adaptability using biosensors

Le Wang, Wei Bai

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 988 , 2025, DOI: 10.62617/mcb988

Abstract：

Physical education plays an essential role in the growth of students’ overall health, fitness, and well-being. Wearable biosensors revolutionize physical performance monitoring by providing real-time data on physiological parameters, providing valuable insights into students’ fitness and flexibility during physical activities. The research aims to develop an approach for assessing students’ athletic adaptation and physical fitness using biosensors. Traditional monitoring systems have complexity in managing the huge volumes of data collected from several sensors because of noise and ambiguity. These research difficulties are addressed with the help of a deep learning (DL) based assessment model, which monitors students’ fitness using biosensor data. This research proposed a novel dynamic Bumblebee mating refined deep neural networks (DBBM-RDNN) to forecast student physical fitness and sports adaptability levels using biosensors. The biosensor dataset provides different data types that capture various aspects of physical activity and fitness. The data was preprocessed using low-pass filters to remove noise from the achieved data. Principal Component Analysis (PCA) is developed to extract the features from preprocessed data. DBBM is utilized to optimize the features in sensor data and RDNN to classify or predict fitness and adaptability levels in students based on data from sensors in real time. In a comparative analysis, the research assessed various performance metrics, such as accuracy (98.05%), precision (90.9%), recall (90.1%), F1-score (88.55%), MAE (1.915) and RMSE (2.505). Experimental results indicate the proposed model achieved superior performance in predicting student physical fitness compared to other conventional algorithms. The research highlights the integration of biosensor technology with DL, which provides an accurate and dependable system for tracking students’ physical performance.

Open Access

Article

Effect analysis of functional physical fitness training based on improved genetic algorithm under functional analysis

Danxu Lu

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1044 , 2025, DOI: 10.62617/mcb1044

Abstract：

In addition to helping athletes enhance their athletic abilities and spark their interest in sports, youth athletics amateur training can also set the groundwork for athletes’ future athletic growth. Physical training still has less than optimal results for Chinese youth, nevertheless. The physical training effect of athletes can be maximized with the aid of amateur training. We can direct the creation of the most sensible physical training plan and choose the best physical training technique in order to achieve the ideal physical training goal and realize the steady improvement of athletes’ physical fitness by focusing more on and analyzing the fundamental and unique physical training strategies. Therefore, in order to improve the scientific and state-of-the-art analysis of training effect and to provide more scientific guidance for youth physical training, this paper introduces scientific quantitative indexes and personalized customized indexes into physical training from the perspective of genetic algorithms.

Open Access

Article

Application research on mechanical assessment and training based on intelligent physical training system in the rehabilitation of athletes’ ankle injuries

Lu Zhang, Zhenzhen Yang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1192 , 2025, DOI: 10.62617/mcb1192

Abstract：

As the only hinge connection between human body and the ground, ankle joint plays an important role in sports. Based on the theory of rehabilitation medicine, this paper puts forward an intelligent physical training system integrating mechanical evaluation and training functions, and applies it to the rehabilitation of athletes’ ankle injuries. The system adopts virtual reality (VR) technology, realizes active ankle rehabilitation training through high-precision sensors and advanced computer simulation technology, and provides accurate evaluation, monitoring and personalized training scheme for ankle rehabilitation. The system creates an immersive training environment for athletes by simulating real sports scenes and processes. The experimental results show that the system is excellent in training convergence speed and performance, and the error is small. Compared with the traditional algorithm, the accuracy is improved by 19.27%. The main contribution of this paper is that the intelligent physical training system integrating mechanical evaluation and training is applied to the rehabilitation of athletes’ ankle injuries, and good rehabilitation results have been achieved.

Open Access

Article

Exploring heart failure treatment via calf & inner thigh electroacupuncture from cell molecular biomechanics perspective within “Three Yin Theories” framework

Hua Yi, Yuting Zhang, Jianhua Yi

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 667 , 2025, DOI: 10.62617/mcb667

Abstract：

Object: To guide meridian external treatment based on the “Three Yin Theories” of Water Warmth, Earth Harmony, and Wood Reaching, and to observe from a cell molecular biomechanics perspective the clinical efficacy of electroacupuncture at the calf (Chuai) and inner thigh in the treatment of heart failure. This involves analyzing how the electroacupuncture might influence cellular and molecular events within cardiomyocytes and related cardiovascular tissues. Methods: Chronic heart failure patients hospitalized in general wards were selected, and the efficacy indices before and after treatment in patients, as well as the differences between groups, were comparatively observed and studied. To explore the mechanism, not only the correlation between the reduction of neuro-endocrine hormone levels and symptom improvement was analyzed through correlation studies, but also the impact on cell molecular biomechanics was investigated. This includes examining changes in the biomechanical properties of the extracellular matrix surrounding cardiomyocytes, as well as alterations in the molecular forces and interactions that govern cell adhesion and communication within the heart tissue. Results: There was a significant difference between the treatment and control groups before and after the treatment (Sig. (two-tailed) < 0.05), and the intergroup difference was not statistically significant (Sig. (two-tailed) > 0.05), failing the significance test. There was a significant positive correlation between the decrease in aldosterone and the decrease in NYHA classification scores and BNP levels; Conclusion: Electroacupuncture at the calf and inner thigh has a better therapeutic effect on heart failure and has certain clinical promotion and application value. From a cell molecular biomechanics standpoint, the treatment appears to modulate key cellular and molecular processes within the heart, potentially providing a new avenue for understanding and enhancing the treatment of heart failure.

Open Access

Article

Impact of biomechanical properties of tongue muscles on accuracy of English vowel pronunciation

Ping Zhang, Xiaoguang Chen

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 937 , 2025, DOI: 10.62617/mcb937

Abstract：

Pronunciation is a complex physiological process. Traditional research usually uses static pronunciation tests and fails to observe the dynamic changes of tongue muscles during pronunciation. This paper aims to comprehensively analyze the structure and function of tongue muscles and their role in English vowel pronunciation from the perspective of tongue muscle biomechanics, and provide a systematic framework for understanding. This paper designs multiple pronunciation tasks to evaluate participants’ pronunciation accuracy and dynamic changes of tongue muscles. Through multi-modal technology, dynamic images and electromyographic signals of the tongue are synchronously acquired to analyze the precise relationship between tongue movement and muscle activity in the pronunciation of English vowels. A tongue biomechanical model is constructed based on finite element analysis and Hill model to precisely simulate the mechanical response of tongue muscle activity and tongue position changes during pronunciation. The experimental results show that there is a significant negative correlation between electromyographic activity and pronunciation quality. The closer the correlation coefficient is to −1, the higher the consistency. The tongue is positioned higher and forward during pronunciation, making it easier to control, so that the pronunciation can be more accurate with less deviation. The greater the movement and flexibility of the tongue, the better it is able to form clear vowel pronunciations. In short, the tongue muscles achieve precise control of tongue position through the coordinated action of internal and external muscles during vowel pronunciation, which is beneficial to improving pronunciation accuracy.

Open Access

Article

Study on the influence of sports participation on happiness from the perspective of biological sports resource allocation in the Yellow River Basin perspective

Haifeng Guo, Yimei Guo, Junhui Ma

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1043 , 2025, DOI: 10.62617/mcb1043

Abstract：

The relationship between physical activity and human well-being is based on biological mechanisms, and regular exercise positively affects physiological, psychological and social health dimensions. This study explores the impact of physical activity resource allocation on residents’ well-being in the Yellow River Basin from a biological basis. Using data from CGSS2015, CGSS2017, and SSY2017, the study combines OLS multiple linear regression modeling and spatial econometrics techniques to reveal how the accessibility of fitness infrastructure, sports services, and resource distribution can enhance well-being by facilitating increased sports participation. Findings reveal significant spatial agglomeration effects, suggesting that a balanced distribution of sport resources can optimize regional health outcomes. However, differences in resource distribution prevent physical activity from yielding physiological and psychological benefits across provinces.

Open Access

Article

Research on the effect of biosensing technology on the dissemination of health information in ideological and political education

Ruirui Zhao

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1093 , 2025, DOI: 10.62617/mcb1093

Abstract：

Biosensing technologies, which monitor physiological responses such as Heart Rate Variability (HRL), Skin Conductance Level (SCL), and Electroencephalogram (EEG) activity, offer a novel approach to enhancing the dissemination of health information in ideological and political education (IPE). In this context, health information encompasses topics such as mental health, stress management, and healthy lifestyle practices, all crucial to students’ overall well-being. Traditional health education methods cannot often capture real-time physiological and emotional responses, which can improve engagement and learning outcomes. This research explores the effectiveness of biosensing technology in enhancing the dissemination of health information within IPE. It examines how physiological data can be utilized to assess student engagement, emotional responses, and learning outcomes related to health. A mixed-methods approach was adopted, combining quantitative data from wearable biosensors (heart rate monitors, Galvanic Skin Response (GSR) sensors, EEG headsets) with qualitative feedback from students. Physiological data were preprocessed using signal filtering techniques, such as the Savitzky-Golay Filter, and features such as heart rate variability, skin conductance, and EEG alpha waves were extracted using the Kalman Filter (KF). A Modified Runge-Kutta Optimizer Integrated with Deep Belief Networks (MRKO-DBN) classifier was employed to predict student engagement based on these features. The research revealed that physiological responses, particularly heart rate variability and skin conductance, were strongly correlated with student engagement. The MRKO-DBN model achieved accuracy in predicting engagement. Qualitative feedback further confirmed that Biosensing technology significantly improved students’ engagement. Integrating Biosensing technology into health education within ideological and political contexts offers significant potential for enhancing student engagement and learning outcomes. By providing real-time, personalized feedback, it fosters a more interactive and responsive learning environment.

Open Access

Article

Integrating ecological philosophy into ideological and political education in universities: Bridging with biomechanics for sustainable development and human health considerations

Qin Zhang, Lingzhen Zhao

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 710 , 2025, DOI: 10.62617/mcb710

Abstract：

The ideological and political education (IPE) ecosystem in universities is not only an essential component of the broader educational ecosystem but also a microcosm of it. In an era that emphasizes ecology and sustainability, integrating the concepts of the biomechanics field into the ecological environment of IPE in universities holds significant practical implications. Biomechanics, a discipline dedicated to studying the mechanical behavior of organisms, has a profound impact on aspects such as the ecological environment and human health. From the perspective of ecological philosophy, the ecological environment of IPE in universities should fully consider the sustainable development of biomechanical technologies and their influence on human health. This paper presents a dynamic early warning system for IPE in universities based on an improved Support Vector Machine (SVM) algorithm. This system aims to optimize the IPE model and enhance educational effectiveness while incorporating concepts related to biomechanics. We have constructed an evaluation index system for the quality of IPE in universities across five dimensions: basic quality, teaching attitude, teaching method, teaching ability, and teaching effect. These indicators are evaluated through expert scoring to generate a comprehensive assessment of the teaching quality of IPE. Taking into account the close connection between human mechanical responses and the ecological environment in the field of biomechanics, during the evaluation process, we incorporate the impact of the ecological environment on the human biomechanical state (such as bone development and muscle function) into consideration. This approach guides students to establish a correct ecological view and understanding of biomechanical technologies. Model simulations and performance verifications show that the fuzzy neural network undergoes 779 training iterations, with a training target set at 0.05 and a learning rate of 0.09. This model demonstrates a strong ability to provide comprehensive dynamic early warnings for IPE in universities. It has obvious advantages in adaptability, model fitting accuracy, and processing efficiency in the face of information overload, contributing to the continuous development of IPE in universities from the integrated perspective of ecological philosophy and biomechanics.

Open Access

Article

College sports offline and online mixed teaching evaluation enhanced by biomechanics and GA-BP neural network

Xu Han, Bin Wang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 904 , 2025, DOI: 10.62617/mcb904

Abstract：

In the process of higher education reform, physical education plays a vital role in improving students’ comprehensive quality. The online hybrid teaching mode integrates the advantages of online and traditional teaching, which has been gradually applied to various teaching scenarios. However, establishing a comprehensive and effective evaluation model for hybrid teaching remains a challenge due to its complexity. This study introduces a teaching evaluation model based on the Genetic Algorithm Optimized Back Propagation (GA-BP) neural network, incorporating the principles of biomechanics to enhance the evaluation of motor skills, movement efficiency, and physical performance. By comparing the BP and GA-BP models using sample data, results demonstrate that the GA-BP model provides higher precision, offering a feasible framework for hybrid teaching quality evaluation. This integration of computational methods and biomechanical insights not only enriches the model’s applicability but also advances the evaluation of physical education quality and athletic performance.

Open Access

Article

Understanding the biomechanics of smartphone addiction: The physical and cognitive impacts of prolonged device use on college students

Qiufang Sheng

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 650 , 2025, DOI: 10.62617/mcb650

Abstract：

The widespread use of smartphones, particularly among college students, has raised concerns about the negative impacts of prolonged device use on physical and cognitive health. While smartphones offer many conveniences, excessive usage can lead to a range of biomechanical and psychological issues, including posture-related strain, repetitive strain injuries (RSIs), eye strain, impaired cognitive function, and elevated levels of anxiety and stress. This study aims to examine the physical and cognitive impacts of prolonged smartphone use among college students, focusing on biomechanical strain, cognitive impairments, and psychological effects. It explores the relationship between smartphone addiction and its effects on posture, musculoskeletal health, eye fatigue, focus, memory retention, and mental health. The study was conducted with a sample of 37 college students in China. Data collection involved physical assessments, including posture analysis, musculoskeletal screening, and cognitive assessments, such as focus and memory tests. Mental health was evaluated using standardized surveys for anxiety, stress, and depression. Statistical analyses were used to interpret the data, including descriptive statistics, paired t-tests, correlation analysis, and multiple regression. The results indicated a significant increase in neck tilt angle, posture discomfort, and wrist strain over the study period, with higher smartphone usage correlating with worse physical outcomes. Cognitive performance, mainly focuses and memory retention, significantly declined with increased smartphone usage. In addition, elevated levels of anxiety and stress were observed among heavy smartphone users, with a strong correlation between high smartphone usage and negative psychological effects.

Open Access

Article

Biomechanical application research on cognitive health management in the elderly based on data analysis and intelligent coordination in the age of artificial intelligence

Dongxian Yu, Guoke Qiu, Ming Li

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 772 , 2025, DOI: 10.62617/mcb772

Abstract：

The conventional approach to elder care is no longer able to satisfy the rising need for medical attention for the elderly due to China’s aging population. The demographic trait of “getting old before getting rich” presents a challenge to the distribution of social healthcare resources, as this article first examines the current pattern of changes in the composition of the older population. The community-based “healthcare integration” paradigm of senior care services has emerged as a successful remedy in this regard. Drawing on biomechanical principles, we can envision the community healthcare system as a complex “biomechanical network”. In order to categorize and predict the health data of the elderly, this study constructs a mathematical model akin to analyzing biomechanical forces and movements. By employing methods similar to optimizing structural loads, such as the CART decision tree and support vector machine (SVM) optimization, we enhance the model’s precision. Just as biomechanical systems adapt to varying loads, our model adapts to handle complex health data. By building the optimal classification plane of the support vector machine and adding relaxation variables, the model application solves the classification problem of linearly indivisible data, further enhancing the model’s accuracy and effectiveness, much like how a biomechanical structure self-adjusts to external pressures. In this paper, a geriatric health service platform based on information technology, including big data and the Internet of Things (IoT), is formed. The service system is a tripartite linkage disease management service model that covers the synergistic cooperation of community hospitals, third-party enterprises, and the streets where they are located. A prediction model for common cases, such heart disease, was developed by preprocessing and cleaning the data of 2311 valid samples from the China Geriatrics Center. The dataset was then characterized. The findings demonstrate the model’s high operability and accuracy in predicting health and managing long-term care for older people who are mobility. In the context of an aging society, by integrating biomechanical insights into the design of this healthcare model, the research not only establishes a theoretical foundation for community health care integration but also provides valuable references for implementing digital senior care services and enhancing health management for the elderly in an aging society.

Open Access

Article

Parameter optimization of membrane mlectrode assembly in Fuel Cell based on improved differential evolution algorithm: biomechanical stress and strain considerations

Ting Lu, Yan Liu

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1035 , 2025, DOI: 10.62617/mcb1035

Abstract：

The membrane electrode assembly in a proton exchange membrane fuel cell (PEMFC) functions as the electrochemical reaction region, where the generated electric current relies on the diffusion of reactant gases and electron conduction. Drawing inspiration from biomechanics, this study embarked on constructing a database of PEMFC performance data. Similar to how biomechanical studies use advanced imaging and sensing techniques to map the internal workings of organisms, three-dimensional computational fluid dynamics (CFD) simulations were employed to capture the intricate fluid and gas behaviors within the fuel cell. The data was then used to train data-driven surrogate models based on artificial neural network (ANN) and improved differential evolution for rapid prediction and optimization. When considering the biomechanical aspects, we analyze the mechanical stresses and strains that occur within the membrane electrode assembly during operation. These biomechanical factors can affect the durability and performance of the fuel cell. The gas diffusion layer (GDL) is similar to the pore structure in biological tissues. The pore structure of biological organisms, such as bones, not only ensures the diffusion and transport of nutrients, but also provides space for the attachment of cells to maintain the growth and metabolism of bones. The optimization results revealed that the pores of the GDL, just like the pores of biological tissues, affect the diffusion efficiency of the reactant gases (similar to nutrients) to the catalytic layer, and an appropriate porosity ensures the supply of the reactants required for the electrochemical reactions inside the cell, and improves the PEMFC performance of the cell. By utilizing the random forest algorithm (RF) to conduct feature importance evaluation, we can gain further understanding and interpretation of the factors influencing coupling relationships. The researchers successfully identified the optimal values of GDL porosity and thickness, resulting in an 8.75% increase in power density and significant improvement in oxygen distribution uniformity. To validate the effectiveness and accuracy of the optimization, the optimized structural parameters were incorporated into CFD simulations. The validation results demonstrated close alignment between the optimized model's performance and actual values, confirming the efficacy and reliability of the optimization framework. Overall, this data-driven optimization approach provides an effective tool for multi-variable optimization of complex systems and holds significant importance in enhancing the performance and power density of PEMFC, while also taking into account the biomechanical factors that influence its long-term operation and stability.

Open Access

Article

Design of an intelligent English learning platform combining biomechanical analysis with biological data analysis and text semantic matching

Hongming Zhu

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 856 , 2025, DOI: 10.62617/mcb856

Abstract：

Intelligent classrooms have demonstrated significant promise in enhancing learning efficiency as a result of the quick development of big data and artificial intelligence technologies. This study proposes a text semantic matching model (OM) that combines deep learning and K-means clustering algorithm, aiming to optimize vocabulary. Importantly, it delves into the biomechanical aspects of learning by considering how physical and physiological processes interact with language acquisition. By mimicking the learning mechanism of biological neural networks and further exploring the biomechanical correlates of neural activity during learning, such as the muscle tensions and postural changes associated with cognitive efforts, this model simulates how the brain processes and stores language information. These biomechanical factors can have an impact on concentration and fatigue levels, which in turn affect semantic understanding and memory performance during the learning process. The experimental results indicate that this method not only improves teaching effectiveness, but also provides a solid foundation for future research on intelligent language learning environments, taking into account the biomechanical underpinnings of learning.

Open Access

Article

Comprehensive evaluation of health community construction based on biomechanical perspective

Xiang Hu, Yonghong Lan

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1025 , 2025, DOI: 10.62617/mcb1025

Abstract：

The comprehensive evaluation of healthy community construction is an important means for managers and decision-makers to understand the development of community health within their jurisdiction, and also a scientific basis for formulating practical and feasible health policies and health development plans. Scientific evaluation of the overall level and differences in the construction of healthy communities has important theoretical significance and reference value. Based on the principal component clustering analysis method as well as the theoretical foundation, the multiple evaluation indicators in the evaluation index system of health community construction are standardized and dimensionally reduced. At the same time, the principal component factor load matrix clustering analysis is used, combined with the practical significance and evaluation direction of the indicator categories, to propose a design idea for the classification index system. The comprehensive principal component evaluation and clustering analysis are used to quantitatively examine the level of health community construction in specific regions and make horizontal comparisons, provide theoretical support and decision-making reference for the construction of healthy communities. The correctness and effectiveness of the proposed method system were verified by numerical examples.

Open Access

Article

Analysis of the public art value of Huizhou three carvings from the perspectives of biomechanics and biology: Digitization, inheritance, and their impact on the development of museum city

Luming Wang, Le Su

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 878 , 2025, DOI: 10.62617/mcb878

Abstract：

This paper explores the three carvings in Huizhou from a novel perspective integrating cell molecular biomechanics. Taking the stone carving, wood carving, and pottery carving of the Ming Dynasty as examples, after gathering relevant literature via the network and classification, microscopic and scanning techniques were employed. The granite used in stone carving, at a cell molecular level, consists of silicate minerals with strong covalent bonds. These bonds endow the stone with hardness and resistance to deformation. The cells and molecules within the granite are arranged in a crystalline lattice, which dictates its mechanical properties. Mahogany in wood carving has cellulose and lignin molecules. The lignin provides rigidity and hydrophobicity, protecting the wood cells from moisture and external mechanical stresses. In pottery carving, the clay particles are sintered together during firing, creating a new molecular structure. The formation of a grease protective film and oxide on the brick carving is a result of molecular interactions at the surface. This layer can be seen as a self-assembled molecular barrier, similar to how cell membranes protect cells. The axisymmetric modeling and downward center of gravity influence the stress distribution at a molecular scale. A streamlined shape may reduce air or fluid resistance, minimizing mechanical forces acting on the carving's surface molecules. The delicate material with small particles implies a specific microstructure that affects its mechanical behavior.  Understanding these cell molecular biomechanical aspects not only reveals the hidden scientific secrets of Huizhou carvings but also aids in their conservation and restoration. It enriches our comprehension of their durability and aesthetic qualities from a microscopic and molecular vantage point, further enhancing their cultural and digital significance in the context of the museum city's development.

Open Access

Article

Accumulation of trace elements in tea under different soil conditions and the biomechanics-related mechanism of their influence on plant antioxidant enzyme activities

Shengfeng Zhang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 944 , 2025, DOI: 10.62617/mcb944

Abstract：

China is an important tea-growing country, and top quality tea, specialty tea and other high-quality tea is more and more favored by the tea industry, so that the production demand is rising year by year. The formation of high quality tea requires suitable soil factors, and soil is one of the two key factors affecting the production of high quality tea. The physicochemical properties and nutrient content of different soils can significantly impact the intracellular processes within tea plants. The absorption and transportation of trace elements such as selenium in tea roots are mediated by specific transporter proteins. These proteins operate based on molecular mechanisms and biomechanical forces that drive the movement of ions across cell membranes. In this paper, we utilize GPS technology to design the distribution area of the test tea production area, and adopt the S-type method to collect the soil of tea differential land in different ecological environments, to explore the physicochemical properties, nutrient content, pH value and water management of different soil types. The whole trace elements and effective trace elements in tea were determined through experiments. The antioxidant enzyme activity of tea was measured by TBA and other methods. The results showed that after planting in different soils, the selenium content of autumn tea was 0.08%, 0.04%, 0.04% in loamy soil > sandy soil = clay soil, respectively. The amount of selenium carried out was sandy soil > loamy soil > clay soil, and the amount of selenium carried out increased by 142.37 kg and 94.97 kg after comparing two by two. Compared with the tea leaves with added trace elements, the T-AOC of the tea leaves without added decreased by 18.75%, 14.20%, 28.06%, and 35.14%. These findings highlight the importance of understanding the cellular and molecular processes in tea plants influenced by soil conditions and trace elements for optimizing tea quality and production.

Open Access

Article

Optimization of international talent training program in biological and biomechanical field of Shaanxi universities by integrating Transformer-GRU model under the “Belt and Road” initiative

Jinchao Chen

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1021 , 2025, DOI: 10.62617/mcb1021

Abstract：

In the field of biology of Shaanxi universities, there are problems such as insufficient internationalization of course content, limited internationalization level of teachers, and difficulty in meeting the personalized needs of students’ foreign language ability. To this end, under the Belt and Road Initiative, this paper proposes an intelligent solution based on Transformer and GRU (Gated Recurrent Unit) models, aiming to improve the quality of international education in the field of biology of universities by optimizing course content and teaching methods. This study first uses the Transformer model to integrate and analyze a large number of international education resources, identify global cutting-edge knowledge and cross-cultural education elements in biology courses, including biomechanical principles that underpin biological functions and interactions. This provides scientific support for the optimization of course content. At the same time, the GRU model is used to dynamically analyze the progress of teachers’ international teaching and students’ learning feedback. Just as organisms can adjust their metabolic rate according to the changes in the environment, the model automatically adjusts the pace and difficulty of the subsequent teaching content according to the students’ speed of mastery and difficulties in understanding biomechanics knowledge, ensuring that each student can keep up with the pace of teaching. Additionally, the integration of biomechanical concepts into the curriculum helps students understand the mechanical properties and behaviors of biological systems, fostering interdisciplinary thinking and enhancing their global vision. Experimental results show that the students in Class A who adopt this research program are significantly better than the control Class B in terms of knowledge mastery, interdisciplinary thinking, and global vision ( P < 0.05); after the experiment, the average foreign language ability score of the students in Class A is 7.04 points higher than that of Class B; the overall satisfaction of the students in Class A with the new teaching program is as high as 82.5%. This paper, based on the combination of Transformer and GRU models, can effectively promote the international talent training process of biology majors in Shaanxi universities, particularly by incorporating biomechanical insights, thereby enhancing the competitiveness of this major in global academic and scientific research cooperation.

Open Access

Article

Enhancing supply chain resilience: The role of security practices and performance in mitigating disruptions in ghana’s manufacturing sector

Fugang Guo, Mohd Azwardi Md Isa, Noor Azura Azman

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 688 , 2025, DOI: 10.62617/mcb688

Abstract：

At the current stage, the retail industry is undergoing unprecedented changes. From traditional physical stores to online shopping platforms, and then to the new retail model that integrates online and offline, customers’ demand for shopping experience is constantly changing. To meet these demands, retailers need to constantly explore and apply new technologies to optimize the retail environment and enhance customer experience. Biomechanics is the study of the internal and external mechanical behavior of living organisms, which is concerned with the structure, function and motion laws of living organisms. Applying the knowledge of biomechanics to retail environment design can effectively improve customers’ shopping experience. Based on this, this paper takes intelligent container as an example, gives a visual solution of detecting goods in intelligent container based on deep neural network, and proposes a twin-based pairwise image difference detection algorithm named DiffNet as the core algorithm of intelligent container solution, which aims to help enterprises deploy intelligent container flexibly, safely and at low cost. Enhance the customer’s offline self-service shopping experience.

Open Access

Article

Multi-frequency and multi-system GNSS positioning data fusion algorithm based on Kalman filter

Zerui Chen , Yanhong Xiao , Jiaxiang Ou , Xin Wu , Houpeng Hu , Jian Xiao , Shang Yang, Zhenghao Gao

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 691 , 2025, DOI: 10.62617/mcb691

Abstract：

With the widespread application of Global Navigation Satellite System (GNSS) in the fields of positioning and navigation, traditional single frequency and single system positioning methods are gradually unable to meet the requirements of high accuracy and high reliability. Especially in complex and dynamic environments, GNSS signals are affected by multipath effects, occlusion, and interference, resulting in a significant decrease in positioning accuracy. Therefore, it is particularly important to develop a multi-frequency and multi-system GNSS positioning data fusion algorithm. This article used Kalman filtering technology and combined the data characteristics of multi-frequency and multi-system GNSS signals to study a new positioning data fusion algorithm. By comprehensively processing different GNSS systems and frequency signals, the positioning accuracy and anti-interference ability were significantly improved. The experimental results showed that the algorithm studied improved the average positioning accuracy by more than 6.23% in complex environments compared to traditional methods, and also exhibited good adaptability and stability under dynamic conditions. Fully utilizing the advantages of multi-frequency signals and combining advanced data fusion technology is an effective way to improve GNSS positioning performance, providing new ideas and methods for future intelligent navigation applications.

Open Access

Article

Risk control of sports flooring in athletic activities from the perspective of inertia mechanics

Mengyao Li, Yuyi Ye

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1111 , 2025, DOI: 10.62617/mcb1111

Abstract：

From the perspective of inertia mechanics, sports flooring plays a critical role in controlling safety risks in athletic activities. Firstly, high-quality flooring materials and structural designs can effectively absorb impact forces generated during exercise, thereby reducing the physical burden on athletes and lowering the risk of injury. Secondly, flooring materials with good resilience can provide appropriate rebound properties, offering better support and reaction forces for athletes, thus improving both performance and safety. Additionally, high-quality flooring materials possess high durability and stability, maintaining their performance over prolonged use and minimizing safety hazards caused by material degradation. Lastly, flooring design should account for the characteristics of different sports, providing suitable coefficients of friction and elasticity to meet the needs of various athletes and reduce the likelihood of accidents during sports activities. Therefore, the design and material selection of sports flooring play an essential role in ensuring athlete safety and enhancing athletic performance. The findings of this study have significant implications for future research and practical applications, as they provide a scientific basis for the development of safer, more effective sports flooring solutions that can be tailored to meet the specific needs of different sports disciplines.

Open Access

Article

Ergonomic study of visitors in red cultural venues from a biomechanical perspective: A case study of students from Sichuan University of Arts and Science

Yang Gao

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1132 , 2025, DOI: 10.62617/mcb1132

Abstract：

Red cultural venues are pivotal in preserving China’s revolutionary heritage and fostering national identity. However, these venues often encounter difficulties in engaging contemporary audiences, particularly younger visitors who seek more interactive and technologically enriched experiences. This study investigates the ergonomic and biomechanical challenges faced by young visitors, using students from the ideological and political education program and the cultural industry management program at Sichuan University of Arts and Science as a representative case study. Employing a mixed-methods approach, the research integrates quantitative surveys with 200 participants and qualitative interviews with 30 participants to assess physical discomfort and engagement levels. Statistical analysis reveals that prolonged standing significantly increases discomfort ( β = 0.04, p < 0.001), while higher levels of interactive engagement ( β = −0.30, p = 0.002) and overall satisfaction ( β = −0.20, p = 0.013) are associated with reduced discomfort. Thematic analysis identifies key issues such as leg fatigue, back pain, limited interactivity, and restrictive venue layouts. Based on these findings, the study recommends enhancing interactive exhibits, optimizing spatial layouts, providing additional seating, and expanding venue spaces to improve visitor comfort and engagement. These evidence-based recommendations aim to inform the redesign of red cultural venues, making them more accessible and enjoyable for young visitors, thereby enhancing their educational and cultural impact. This research contributes to the limited literature on ergonomics in cultural venue settings and offers practical implications for improving the accessibility and user-friendliness of heritage sites.

Open Access

Article

Sports training injuries and prevention measures using big data analysis

Yuan Xue, Erjuan Du, Zhihong Hou

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 539 , 2025, DOI: 10.62617/mcb539

Abstract：

This work explores the application of big data technology in monitoring sports training injuries, emphasizing the biomechanical principles underlying injury mechanisms to enhance the accuracy of injury prediction and provide scientific prevention measures. It collects training data from professional sports teams using big data technology and constructs a Bi-directional Long Short-Term Memory (BiLSTM)—Residual Network (ResNet) model through deep learning techniques. In this model, the BiLSTM module captures the temporal sequence features of sports data, while the ResNet module improves the model’s expressiveness and stability through residual learning. To establish a clearer connection with mechanobiology, the study discusses the mechanical forces involved in sports injuries, including impact forces, torsional stresses, and their effects on tissues at the cellular level. By integrating biomechanical insights with big data analytics, the research aims to provide a comprehensive understanding of how mechanical stressors contribute to injury risk. The performance of the proposed model in predicting sports injury risks is evaluated, showing an accuracy of 95.72%, a precision of 91.59%, a recall of 85.40%, and an F 1 score of 88.56%, significantly outperforming existing traditional models and other comparison algorithmsTherefore, the proposed model demonstrates exceptional performance in improving the accuracy of sports injury prediction and providing personalized prevention measures, offering experimental references for the intelligent development of the sports field by bridging sports science and biomechanics.

Open Access

Article

Swimming posture recognition using inertial sensors and CNN-SVM: Unveiling the cellular molecular biomechanics nexus

Chunsheng Xie, Ling Yin, Congying Cui

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 509 , 2025, DOI: 10.62617/mcb509

Abstract：

The biomechanical mechanisms of swimming involve a number of aspects. The forces exerted by muscles during different swimming postures are crucial. These muscle contractions and relaxations follow specific biomechanical principles. This work aims to develop a swimming posture recognition system based on inertial sensors and a Convolutional Neural Network-Support Vector Machine (CNN-SVM) to improve the accuracy and real-time performance of posture recognition. First, an inertial sensor system to be worn on swimwear is designed to collect three-axis motion data, including acceleration, angular velocity, and magnetometer readings. The collected data are then preprocessed through denoising, normalization, and feature extraction steps to ensure high-quality input data. Next, a Convolutional Neural Network (CNN) is constructed to automatically extract high-level features from the preprocessed sensor data. The CNN model, through multi-layer convolution and pooling operations, effectively captures the spatiotemporal patterns in the motion data, extracting highly distinguishable features for posture recognition. To further improve the model’s classification performance, a Support Vector Machine (SVM) classifier is applied based on the CNN model. Specifically, CNN is responsible for feature extraction, while the SVM handles the final posture classification. Cross-validation is used to train and validate the model, assessing its performance. Experimental results show that the model achieves a 95% accuracy rate on the training dataset and maintains an accuracy rate above 93% on the test dataset. The system can accurately and in real-time recognize various swimming postures, including freestyle, breaststroke, backstroke, and butterfly. The recognition accuracy for all four swimming styles exceeds 91%. Understanding these biomechanical mechanisms helps in improving the accuracy of the recognition system. In summary, the proposed method for swimming posture recognition based on inertial sensors and CNN-SVM has significant advantages in accuracy and real-time performance. It allows for better interpretation of the sensor data and more precise identification of different postures. The high accuracy and generalization ability of the proposed system suggest that it can effectively capture and analyze the biomechanical nuances of swimming, providing valuable insights for swimming training and performance evaluation, and opening up new avenues for intelligent sports monitoring. evaluation.

Open Access

Article

Exploring the impact of metaverse-enhanced sports biomechanics on HIIT performance and psychological well-being

Yucai Gao, Qiuyu Yu, Yuqi He, Wenjing Xu, Dongyu Zhang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1259 , 2025, DOI: 10.62617/mcb1259

Abstract：

The study explored the advantages of combining medium-range enhanced exercise biomechanics with high-intensity interval training (HIIT). Using new technologies such as virtual reality (VR) and augmented reality (AR), the research deepens biomechanical analysis techniques to enable instant feedback of athlete training data. The integration of biomechanical analysis is widely reflected in HIIT performance parameters, including speed change, endurance improvement, and overall exercise performance. In the process of technology intervention training, the virtual world environment shows a unique psychological auxiliary function, involving the enhancement of motivation, participation degree and psychological adjustment. The research data reveal that the meta-enhanced biomechanics technology has a good performance in improving sports performance and mental state, and this training mode is opening the innovative direction of sports training system.

Open Access

Article

Recognition of foot footwork based on dual model convolutional neural network-driven biomechanics patterns

Weihong Shen

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 638 , 2025, DOI: 10.62617/mcb638

Abstract：

Today, with the increasing popularity of football, more and more scholars will focus on using the digital and systematic management methods of football to further improve the safety and effectiveness of football. Similar to how cells within an organism operate in a highly coordinated and biomechanically regulated manner, football players' movements also involve complex biomechanical processes. Establishing a football data analysis system and guiding athletes is like understanding and modulating the molecular interactions and mechanical forces within cells to optimize their function. However, the current such systems are mostly based on video monitoring technology, and their actual operation process is limited by the deployment environment and expensive. In order to realize the widespread popularity of football movement analysis, this paper uses intelligent wearable devices, based on dual model convolutional neural network (DMCNN) for football players virtual step (behind), step (puskash), push progress (sliding), test (inside and outside cycling) and jump (Ronaldo), and by adjusting the convolutional core size and convolution step parameters optimize neural network performance. The resulting algorithm model, which outperforms the K nearest neighbor (KNN) and support vector machine (SVM) algorithms, provides a more accurate understanding of football players’ biomechanical patterns, just as advanced cell molecular biomechanics techniques offer deeper insights into cellular behavior and function, potentially leading to more refined training regimens and injury prevention strategies in football.

Open Access

Article

Sports training injury risk assessment model based on biological mechanisms and complex network analysis

Changyuan Yin, Ting Luo, Zhenping Ye

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 653 , 2025, DOI: 10.62617/mcb653

Abstract：

To improve the accuracy and practicality of sports training injury risk assessment (IRA), this paper constructs a model based on a complex network analysis algorithm and conducts performance comparison experiments across multiple dimensions. The research results demonstrate that the optimized model performs well in terms of risk assessment accuracy, real-time processing, robustness, adaptability, and user satisfaction. Specifically, the Area Under Curve of the Receiver Operating Characteristic Curve (AUC-ROC) of the optimized model reaches 0.928, indicating high accuracy in risk assessment. In addition to these metrics, this study includes a discussion on the biological mechanisms underlying sports injuries, emphasizing how biological signals can be integrated with the complex network analysis to enhance the model's predictive capabilities. This integration allows for a more comprehensive understanding of injury risk factors, such as muscle fatigue, joint stress, and tissue response, which are critical for effective injury prevention strategies. In the real-time experiment, the processing speed score is 4.9. In the robustness experiment, the fault recovery ability score is 4.3. In the adaptive experiment, the diversified data processing ability score is 4.5. In the user satisfaction experiment, the accuracy score of risk assessment is 4.9, and the convenience score is 5.0. These results indicate that the optimized model has significant advantages in handling complex data and adapting to changing environments. Therefore, this paper provides valuable insights for improving injury risk management and decision support in sports training by incorporating biological insights into the assessment model.

Open Access

Article

Latent profile analysis of parent-child triangulation: unveiling the behavioral nexus in adolescents’ internalized and externalized problem behaviors

Chao Qu, Haidong Zhu

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 840 , 2025, DOI: 10.62617/mcb840

Abstract：

Parent-child triangulation is a pattern of negative parent-child relationships in which children are passively or actively involved in family conflict, which may lead to behavioral problems in adolescents. Latent profile analysis was used to explore the relationship between potential categories of parent-child triangulation and internalized and externalized problem behaviors in a sample of 1361 middle school students. The results showed that: (1) parent-child triangulation can be divided into four potential types according to the extent to which adolescents perceive it: low-profile equilibrium (26.89%), high parentification profile (28.07%), medium-profile difference (30.64%), and high-profile difference (14.40%); (2) adolescents with a low-profile equilibrium and high parentification profile have the lowest level of internalized problem behaviors, but the externalized problem behaviors of the high parentification profile were significantly higher than those of the low profile; the adolescents with a medium profile had a high level of both internalized and externalized problem behaviors, and the adolescents with a high profile had the highest level of both internalized and externalized problem behaviors; (3) the younger the age and the younger the adolescents living in towns, the less likely they were to perceive parent-child triangulation, and the highest level of parentification was found among boarding school students. Moreover, this research extends its scope by considering the biomechanical aspects. This holistic approach may provide new insights into the underlying mechanisms and potentially inform more effective intervention strategies.

Open Access

Article

A biomechanical perspective on the relationship between basketball performance and college students’ physical and mental health: An integrated analysis of athletic performance and psychological regulation

Wei Wang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1231 , 2025, DOI: 10.62617/mcb1231

Abstract：

This study delves into the integration of biomechanics in analyzing basketball performance and its profound impact on the physical and mental health of college students. By focusing on biomechanical factors influencing athletic performance, the research investigates how basketball, as a dynamic physical activity, contributes to improving physical fitness and mental well-being. Through advanced biomechanical analysis, the study examines key aspects such as joint kinematics, muscle activation patterns, and force distribution during basketball movements like jumping, running, and shooting. These insights provide a deeper understanding of how proper body mechanics—such as optimized alignment, enhanced movement efficiency, and effective load management—can elevate athletic performance and reduce the risk of injuries. The research further explores the relationship between students’ physical fitness and mental health, identifying prevalent psychological challenges among college students, including anxiety, depression, and interpersonal sensitivity. By integrating biomechanical evaluations with psychological assessments, the study highlights how the optimization of movement mechanics in basketball can promote physical endurance and agility while fostering psychological resilience and reducing stress. For example, improvements in core stability and proprioception not only enhance sports performance but also support mental clarity and emotional regulation. The findings advocate for incorporating biomechanics-informed physical education programs, particularly those centered on basketball, into university curricula. Such programs could utilize technologies like motion capture systems and wearable sensors to monitor and improve students’ biomechanical efficiency while simultaneously addressing their psychological needs through structured physical activities. This integrated approach underscores the dual benefits of sports for physical and mental health, providing actionable insights into how biomechanics can be leveraged to optimize athletic performance and promote holistic well-being among college students.

Open Access

Article

A study of the effect of fatigue state on soccer players’ shooting movements based on Mediapipe

Haidong Wang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1361 , 2025, DOI: 10.62617/mcb1361

Abstract：

Soccer is recognized as one of the most widely played and commercially significant sports globally. An athlete’s performance is typically impaired during states of fatigue. Investigating the body mechanics of soccer players under states of fatigue can provide insights for coaches regarding the physical capabilities and movement deficiencies of their athletes. This understanding can facilitate the adjustment of game strategies and the development of tailored training regimens following competitive matches. Advancements in artificial intelligence have led to the maturation of image recognition technologies, which are increasingly applied across various industries, including promising applications within the realm of soccer. Consequently, this study analyzed a cohort of 5 amateur soccer players (mean age 19.8 years; mean height 1.82 m; mean weight 73.6 kg). The study involved participants who completed 10 shootings on goal as a control group before the implementation of a fatigue protocol, followed by an additional 10 shootings on goal as an experimental group after the completion of the fatigue protocol. Mediapipe image recognition tools and high-speed cameras were utilized to capture data on the various skeletal nodes of the athletes’ bodies and the velocity of the shooting ball, which were subsequently analyzed. The results of the study revealed that when in a state of fatigue, there were significant alterations in the angular displacement of the hip and knee joints in comparison to the ankle joint during shooting by soccer players. The decreased angular displacement of the hip and knee joints resulted in inferior contact between the foot and the ball, as well as a reduction in the speed applied to the ball, leading to a decline in shooting accuracy and ball speed. The findings substantiate the impact of fatigue on the shooting movements of athletes.

Open Access

Article

Biosensors on teaching quality in applied higher education institutions from a biomechanical perspective

Hong Liu

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1293 , 2025, DOI: 10.62617/mcb1293

Abstract：

This study examines the impact of wearable biosensor technology on student engagement and academic performance in educational settings. The purpose was to investigate how experience with biosensors influences engagement levels and whether this engagement correlates with academic success. Key issues addressed include the unexpected negative correlation between biosensor experience and academic performance, indicating that reliance on technology may not always enhance learning outcomes. Innovative aspects of this research involve identifying the complex relationship between technology use and educational effectiveness, underscoring the need for strategic integration. Proposed solutions include enhanced educator training and active learning strategies that effectively utilize biosensors. The feasibility of these solutions is supported by existing literature on effective teaching practices. Ultimately, findings highlight the importance of thoughtful technology integration to foster meaningful learning experiences.

Open Access

Article

The effects of table tennis on the eyesight of primary and middle school students: A meta-analysis

Wei Shen, Ming Li, Jie Wu, Huihui Xie, Li Liu, Han Li

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1099 , 2025, DOI: 10.62617/mcb1099

Abstract：

Objective: To systematically evaluate the influence of table tennis on the eyesight of primary and secondary school students. Methods: Literature research was conducted by computerized search of CNKI, Wanfang, and VIP databases, Web of Science, Embase, PubMed, and The Cochrane Library databases for randomized controlled trials on table tennis exercise on students’ visual health. Traditional Meta-analysis, subgroup analysis and sensitivity analysis were performed sequentially using Stata 17.0 and Review Manager 5.4 (RevMan5.4 for short). Results: A total of 11 papers with 670 study participants were included for analysis. The effect of table tennis exercise on students’ visual acuity improvement was statistically significant in the experimental group compared to the control group, whose total effect of the literature showed that the left eye [SMD = 1.41, 95% CI (0.95, 1.87), Z = 6.02, P < 0.001] and the right eye [SMD = 1.59, 95% CI (1.08, 2.11), Z = 6.07, P < 0.001] ; subgroup analysis also showed that table tennis sport intervened on left eye vision [SMD = 1.51, 95% CI (0.89, 2.13), P < 0.001] and right eye vision [SMD = 1.72, 95% CI (1.01, 2.42), P < 0.001] in primary school students versus table tennis sport in secondary school students’ left eye vision [SMD = 1.23, 95% CI (0.68, 1.78), P < 0.001], and right eye visual acuity [SMD =1.33, 95% CI (0.99, 1.67), P < 0.001] were statistically significant for prevention and protection of vision. Conclusion: Table tennis exercise interventions have been shown to have a positive effect on preventing and protecting the visual health of primary and secondary school students, and different table tennis exercise cycles, exercise duration, and frequency of exercise and other sports also have a significant effect on preventing and protecting the visual health of primary and secondary school students.

Open Access

Article

Comparative study on psychological characteristics and biomechanical indicators of rock climbers at different levels: An analysis based on self-efficacy, sport motivation, and muscle function performance

Qi Liu, Wenzhi Hou

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1062 , 2025, DOI: 10.62617/mcb1062

Abstract：

Background: Rock climbing is a comprehensive sport that integrates physical strength, coordination, and psychological resilience. Significant differences may exist in the psychological states and biomechanical performance of athletes at different levels. However, systematic studies on the psychological characteristics and biomechanical indicators of rock climbers at different levels remain limited. Objective: This study aimed to compare the psychological indicators (e.g., self-efficacy and sport motivation) and biomechanical characteristics (e.g., muscle activation levels, relative peak torque, and flexor-extensor peak torque ratios) of rock climbers to explore the differences and intrinsic relationships between athletes of different skill levels. The findings aimed to provide a theoretical basis for optimizing performance and designing training strategies. Methods: Twenty-two rock climbers participated in the study, including 11 elite athletes and 11 novice athletes. Psychological indicators were assessed using standardized questionnaires, including self-efficacy and five dimensions of sport motivation: Fun motivation, ability motivation, appearance motivation, health motivation, and social motivation. Biomechanical data were collected using the Noraxon DTS surface electromyography (sEMG) system and the Biodex System 4 isokinetic dynamometer, which measured muscle activation levels and the relative peak torque and flexor-extensor peak torque ratios of the shoulder, elbow, hip, knee, and ankle joints at speeds of 60°/s, 120°/s, and 180°/s. Muscle activation signals were normalized as %MVC, and peak torque values were extracted for analysis. The data were grouped by athlete level, and independent sample t-tests were conducted to compare group differences, with significance set at p < 0.05. Results: Elite athletes demonstrated significantly higher psychological indicators than novice athletes, particularly in self-efficacy (3.19 ± 0.671 vs. 2.77 ± 0.341) and fun motivation (3.28 ± 1.049 vs. 2.78 ± 0.47). Additionally, elite athletes exhibited higher muscle activation levels and relative peak torque in upper limb and core muscle groups compared to novice athletes ( p < 0.05), indicating superior strength control and coordination. Conversely, novice athletes had relatively higher peak torque in lower limb muscle groups but showed deficiencies in strength balance and coordination. Conclusion: Significant differences were found in the psychological states and biomechanical characteristics of rock climbers at different levels. These differences likely contribute to variations in athletic performance. Elite athletes displayed stronger psychological advantages and superior strength in upper limb and core muscle groups. In contrast, novice athletes needed to enhance sport motivation and improve upper limb and core strength to develop comprehensive athletic abilities. This study provides a scientific basis for optimizing training strategies for rock climbers at different levels and lays a foundation for future research on the mechanisms underlying climbing performance.

Open Access

Article

Research on recognition of Wushu motion boxing method based on PSO-BP neural network

Jianhui Wang, Peiyuan Li, Shichun Li, Yufeng Sun, Dengyue Li

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 835 , 2025, DOI: 10.62617/mcb835

Abstract：

Wushu movement full hair is a kind of fitness activity, and it is one of the ways for people to cultivate their self-cultivation and sentiment. It is of great significance to use motion capture system and data gloves to capture human movement posture and guide boxing practice in real time. The research of this topic uses neural network technology to construct a complete recognition framework of martial arts movements. Firstly, the collected martial arts movements are sorted out and a database is constructed. Because of the inherent defects of traditional BP algorithm, this is also because during the training of the modified algorithm, The network converges slowly, and easy to receive local minimum constraints, so this topic uses particle swarm optimization algorithm to optimize the initial weights and improved neural network algorithm to improve the learning rate and increase the reliability of the algorithm. Finally, through the martial arts action boxing recognition framework for testing, it is determined that the proposed algorithm is more effective.

Open Access

Article

A study on the consumption behavior of community group buying leaders in selling agricultural products—From a biomechanical perspective

Yingbo Wang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 896 , 2025, DOI: 10.62617/mcb896

Abstract：

This article explores how group leaders in community group buying influence consumer behavior regarding agricultural product purchases, analyzing their psychological motivations and relational mechanisms. The concept of biomechanics offers a novel and illuminating perspective to understand this phenomenon. First, the article defines the role and functions of community group leaders in promoting agricultural products. It examines the leaders’ promotional actions and behaviors as research subjects, selecting representative traits to analyze their specific effects on consumers’ decisions to purchase agricultural products endorsed by these leaders. Combining qualitative and quantitative research methods, the study conducts field interviews and surveys among community group buying users. The Theory of Planned Behavior (TPB) model is employed to test hypotheses, SPSS software is utilized for descriptive statistical analysis and reliability and validity testing, and AMOS software is used to construct a structural equation model to investigate consumer behavior in purchasing agricultural products promoted by group leaders. In summary, this study aims to unravel the mechanisms underlying consumers’ purchasing behaviors of products promoted by group leaders. From a biomechanical perspective, the linguistic and behavioral promotions of group leaders act as powerful stimuli. Their words and actions can be seen as biomechanical signals, much like the chemical signals insects use to communicate. For instance, a leader vividly describing the taste and texture of a freshly harvested fruit is equivalent to a bee releasing a pheromone trail to guide its fellows to a food source. By analyzing how these promotional actions shape consumers’ perceptions and expectations of agricultural products, we can draw parallels to how organisms respond to environmental cues. This study thus highlights the opportunities and challenges of group leader-led agricultural product promotion compared to traditional sales models, similar to comparing a newly evolved survival strategy in nature with an established one. Furthermore, in terms of energy efficiency and resource management, just as organisms have evolved to optimize their energy use, community group leaders must also streamline their operations. They need to balance the energy expended in promotion, coordination with suppliers, and logistics, similar to how a migrating animal conserves energy during its journey. By efficiently allocating resources, they can enhance the overall success of agricultural product promotion within the community, creating a sustainable model that benefits both consumers and the local agricultural economy, all while being inspired by the principles of biomechanics.

Open Access

Article

Resource construction of intelligent design based on artificial intelligence bio-perception in the protection of intangible cultural heritage

Bin Wang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 986 , 2025, DOI: 10.62617/mcb986

Abstract：

The protection of intangible cultural heritage (ICH) is not only respect and protection for traditional culture, but also plays a vital role in cultural inheritance, social identity, historical memory, economic development, and innovative vitality. With the rapid advancement of globalization and modernization, ICH is also facing unprecedented challenges. However, the traditional protection of ICH has problems such as focusing on static physical protection, insufficient information storage, limited transmission, insufficient modern transformation and innovation, excessive restoration of traditional elements and conservative protection. In response to the above problems, this paper designs an ICH resource construction system based on artificial intelligence (AI) biological perception. It can perceive ICH data through multimodal biology, store and reproduce it, perform feature analysis based on biological emotions and emotional interactions, capture the inheritance logic and emotional connotation of culture, and drive the digital modeling of ICH resources with intelligent design. Dynamic ICH content can be superimposed on real scenes to facilitate education and dissemination, and personalized ICH story content can be recommended based on user preferences to enhance the display and dissemination capabilities of ICH. The results show that the system uses multimodal perception and stores more than 100,000 ICH data items in four major categories and multiple subcategories, and designs a unique interactive tag cloud for users to choose from. When making recommendations for users, it recommends 200 ICH contents to users from the sorted list simultaneously, and the proportion of users clicking on the recommendations reaches 85%, while also achieving the widespread dissemination of ICH in Asia. Compared with traditional ICH protection, this study has achieved efficient digital storage of ICH content, strong modern conversion, and ease of acceptance by users. The scope of dissemination is also wider. This shows that the use of AI and biosensing technology in ICH protection is effective and can contribute to better preservation, publicity and promotion of ICH.

Open Access

Article

Study the role of vertebral artery tortuosity and hemodynamics in the association with headache and cerebrovascular diseases

Qiming Zhou, Chen Feng, Yibin Lu, Dechuan Zhang, Longling Fan

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1101 , 2025, DOI: 10.62617/mcb1101

Abstract：

The complex and unpredictable path of the vertebral artery is closely related to symptoms such as headaches, dizziness, and cerebrovascular diseases. This study aims to explore the role of vertebral artery tortuosity and hemodynamics in the association with headaches and cerebrovascular lesion by quantitatively analyzing the morphological parameters and hemodynamics of the vertebral artery. A total of 85 patients with headache symptoms and vascular lesions identified through computed tomography (CT) scans were included. A comparative analysis was then conducted to assess how different levels of vascular tortuosity affect these hemodynamic parameters. These findings indicate that vertebral artery tortuosity is more prevalent among the elderly, women, and patients with headache and vascular disease. A multivariate stepwise Logistic regression analysis highlights the ratio of the distal diameter to the tortuosity index of the left vertebral artery (d1) as a significant risk factor for headache symptoms in patients with vascular lesions. Hemodynamic analysis reveals complex flow patterns within the highly tortuous left vertebral artery, including vortices at areas of significant vascular tortuosity. The left vertebral artery with a high degree of distortion presents with high time-averaged wall shear stress (TAWSS), a high oscillatory shear index (OSI) region, and a low relative residence time (RRT). This discovery not only provides essential reference information for the morphological and hemodynamic analysis of the vertebral artery but also offers critical predictive insights for future clinical evaluations and interventions targeting patients with vertebral artery tortuosity, aiding in predicting their risk of experiencing headaches or the onset of cerebrovascular diseases.

Open Access

Article

Prevention and rehabilitation training of aerobics sports injuries based on intelligent wearable sensing devices

Junhua Qi, Congying Ge

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1135 , 2025, DOI: 10.62617/mcb1135

Abstract：

Aerobics is a kind of sports activity, which can not only exercise the body but also cultivate the sentiment and reduce the psychological burden. With the improvement of people’s living standards, aerobics is becoming more and more popular, but in fitness activities, there are often some sports injury accidents, which cause certain harm to human health. Therefore, people must take effective precautions against aerobics. Intelligent wearable sensor device is a new high-tech product developed based on Internet technology. It can not only realize real-time monitoring and diagnosis analysis of human body status information, but also combine with mobile terminals such as mobile phones to apply in the field of health management, and also provide personalized services according to user needs. The data collected by the sensor can be used to judge the human health status and exercise situation and make corresponding decisions, to help patients reduce or eliminate the disease burden. It collects the patient’s body data stores it in the database, and then generates corresponding action commands and corresponding motion tracks or speed control modules according to the results fed back by the sensors. At last, it sends these signals to the cloud server to complete the operation process required by the entire system, to achieve the purpose of real-time measurement, processing user health, and assisting athletes in learning training methods. According to human neuroscience, based on intelligent wearable sensing devices, this paper analyzed the prevention and rehabilitation of aerobics injuries and discussed the factors that lead to injuries in aerobics, injury treatment effects, rehabilitation time, and injury treatment satisfaction. The experimental results show that the patient’s satisfaction with the application of intelligent wearable sensing devices in the prevention of aerobics injury and rehabilitation training has increased by 6.84%. The intelligent wearable sensor device realizes the collection and processing of human health data. Applying big data analysis to user behavior analysis, can provide scientific and effective guidance and suggestions for athletes and improve their physical fitness and competitive level.

Open Access

Article

Optimization of isolation and identification methods of antibiotic-producing bacteria from marine microorganisms

Haoran Yang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 815 , 2025, DOI: 10.62617/mcb815

Abstract：

Marine environments are being investigated to identify microscopic forms of life which could produce botanic antibiotics as there is an increasing demand for newer antibiotics which could be used to treat all bacteria due to the ever-increasing resistance of various forms of bacteria. In this study, we enhance the techniques for recovering and characterizing antibiotic-producing bacteria from seawater samples. Seawater samples were obtained from different sea areas, microorganisms were concentrated, and potential antibiotic-producing microorganisms were sought on selective media and in enrichment cultures. Bacterial antibiotic activity screening was performed by agar diffusion assay, and the selected bacteria were characterized with morphological, biochemical and 16S rRNA sequencing methods. Incubation times, temperature, and nutrient media composition were modified, we incorporated biomechanical principles to assess the physical interactions between antibiotic-producing bacteria and target pathogens. Understanding how mechanical forces, such as shear stress in marine environments, influence bacterial growth and antibiotic production can provide insights into optimizing isolation techniques. Furthermore, advancements in bioimaging advance technologies allowed for real-time observation of bacterial behavior and interactions, revealing how physical characteristics, such as motility and biofilm formation, contribute to antibiotic efficacy. Our optimized methods significantly increased the efficiency of isolating antibiotic-producing bacteria, uncovering diverse antibiotic potentials and confirming several novel bacterial species. The integration of biomechanical analysis highlights the promising prospects of marine microorganisms as a source of new antibiotic substances and underscores the effectiveness of combined methods of isolation and identification in the fight against antibiotic resistance.

Open Access

Article

Optimization and bioapplication of deep learning algorithm in the prediction of mechanical properties of metal matrix composites

Tingting Zhang, Manxi Sun, Jiayi Sun, Yi Xu, Yonghong Fu, Yulei Feng

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1324 , 2025, DOI: 10.62617/mcb1324

Abstract：

This study addresses the optimization and bioapplications of a deep learning algorithm for predicting the mechanical properties of metal matrix composites (MMCs), a critical task for efficient material design. And it is also beneficial for deploring more bioapplications of MMCs. Leveraging a comprehensive experimental dataset from multiple research institutions, we employ a Convolutional Neural Network (CNN) for feature extraction and the Recurrent Neural Network (RNN) for sequence analysis. The dataset encompasses mechanical properties such as tensile strength, elastic modulus, and yield strength for diverse MMCs with varying compositions and processing conditions. The research methodology involves rigorous data preprocessing, feature selection, model development, and performance evaluation using metrics like R 2 score, Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), precision, and recall. Addressing the challenge of model robustness and generalizability, we utilize k -fold cross-validation for training and validation. Optimal hyperparameter settings are identified to enhance predictive accuracy. Our results reveal high predictive performance, with R 2 scores ranging from 0.89 to 0.92 for different mechanical properties, thereby demonstrating the model’s efficacy in facilitating material design and optimization processes for MMCs.

Open Access

Review

Integrating sports industry development with national health promotion: A biomechanics-informed study of the healthy China strategy

Gaoyang Zhang, Shunyong Wang

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 807 , 2025, DOI: 10.62617/mcb807

Abstract：

China’s strategic objective of promoting national health is in line with the integration of the sports business with sports promotion programs. Biomechanics, which delves into the mechanical aspects of human movement and its interaction with the surrounding environment, is a linchpin in this integration. When it comes to the construction of sports venues and sports equipment development, biomechanical principles are fundamental. For example, the selection of surface materials for tracks, courts, and fields must consider factors such as ground reaction forces, coefficient of friction, and energy dissipation. These biomechanical parameters not only influence an athlete’s performance but also play a crucial role in injury prevention. Policies promoting the development of sports venues, increasing public access to recreational facilities, and investing in community health programs remain essential for expanding sports participation and promoting fitness. Through an examination of policy frameworks, economic benefits, and social impacts, this study identifies key factors facilitating this integration. Technological advancements, such as the use of inertial measurement units (IMUs) and force-sensitive sensors in sports equipment and training facilities, enable real-time monitoring of biomechanical variables like joint angles, muscle activation, and movement velocities. Public-private collaborations can then leverage these technologies to develop innovative biomechanics-based sports products and services, making them more accessible to the general public. The findings of this study emphasize the necessity of a comprehensive strategy for sports promotion and sector expansion. This strategy should not only focus on economic gains but also aim to achieve superior health outcomes. Biomechanics-informed sports promotion allows for a more in-depth understanding of how different physical activities impact the human body’s biomechanics. This knowledge can be used to customize exercise programs according to an individual’s anthropometric and biomechanical characteristics, ensuring maximum effectiveness and safety. From a social perspective, a health-conscious society with widespread access to sports resources can significantly enhance the quality of life. By minimizing the risk of injuries through biomechanics-optimized sports facilities and equipment, individuals can engage in a more active lifestyle, leading to a reduction in healthcare costs. Moreover, as people participate in sports events, fitness challenges, and wellness campaigns, the shift in public attitudes towards fitness can strengthen social cohesion and community engagement. In conclusion, this study offers recommendations for future legislation and programs to enhance the integration of the sports sector with public health promotion. By fully integrating biomechanics into the development of the sports industry, we can ensure a substantial contribution to the “Healthy China” goals, fostering a more robust sports economy and a healthier society.

Open Access

Review

The integrative role of physical exercise and muscle satellite cells in remodeling muscle structure and function

Yao Lu, Kai Xu, Jianda Kong, Chao Liu

Molecular & Cellular Biomechanics, Vol.22, No.2, 22(2), 1298 , 2025, DOI: 10.62617/mcb1298

Abstract：

With the aging of the population and changes in lifestyle, sustaining muscular function has become essential for enhancing quality of life. Muscle satellite cells, as the principal source of regeneration for skeletal muscles, are essential for muscle growth, maintenance, and repair. Our review explores how physical exercise (PE) impacts the remodeling of muscle structure and function by modulating the activity of Muscle satellite cells (MuSCs), and further identifies the underlying implications of this process for the prevention and treatment of degenerative muscle diseases. By exploring current evidences on the interaction between MuSCs and PE, our review investigating the effect of PE on the activity, proliferation, and differentiation capabilities of MuSCs, and how these changes improve the enhancement of muscle mass and function. Evidences confirmed that PE can enhance the contribution of MuSCs to muscle fibers, particularly by boosting muscle adaptability through changes in muscle fiber type and size. PE-induced activation of MuSCs is linked not only to an increase in the number of muscle fibers but also with promoted endurance and strength performance of muscles. Besides, the positive effects of PE on MuSCs may vary with the form, intensity, and duration of PE. Additionally, PE plays a crucial role in the remodeling of muscle structure and function through the activation and proliferation of MuSCs, stressing the potential value of developing appropriate PE interventions in the prevention and treatment of muscle-related diseases, particularly among the elderly. Future research should further explore the specific effects of various types and intensities of PE on MuSCs activities to maximize exercise prescriptions for strengthening muscle health and function.