Athlete muscle strength control training based on network security and multi-source information fusion
Abstract
With the booming development of competitive sports worldwide, athletic training is receiving increasing interest in the world. Major sports organizations and universities around the world have established their own athlete training centers to support sports training and scientific research activities in recent years. Data from strength training is crucial for controlling muscle strength. However, this key factor is often attacked by the network. As NS threats escalate, artificial intelligence-driven strength training systems encounter information security risks. Therefore, this paper proposed a new strength training method based on NS and Multi-Source Information Fusion (MSIF). This method evaluates athletes’ sports skills, speed quality and strength quality through data fusion algorithm to effectively monitor the activities related to muscle strength control training. The research results showed that under the same conditions, the P value of the indexes of sports skills, speed quality and strength quality of male and female athletes in Group X before and after the experiment was greater than 0.05, and there was no significant difference; the P value of Group Y was less than 0.05, showing a significant difference, and indicating that the relationship between NS and MSIF and athletes’ muscle strength control training was positive.
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