Simulation study on changes of EMG and physiological parameters of athletes under training state based on nano biomechanics analysis

During exercise, the amplitude and frequency of Electromyography (EMG) will change correspondingly, and these changes are closely related to the mode of exercise, the state of exercise and muscle fatigue. Therefore, in order to further study and develop the application of EMG analysis technology in sports practice, this paper combines the physiological characteristics of muscle contraction, uses time-frequency analysis and non-linear analysis to process athletes' surface EMG signals, and tries to evaluate athletes' training level and competitive status. The results show that the eigenmode functions imf and imf3 can effectively reflect the recruitment methods of fast muscle and slow muscle fibre motor units, which will help to evaluate the level of muscle activity and analyse the physiological process of muscle contraction. And the research shows that there is strong nonlinearity in the myoelectric signals of the rectus femoris and medial femoral muscles, while the myoelectrical timing of the biceps muscle is weakly nonlinear. The test results are a strong support for the hypothesis that physiological changes in muscle strength are related to muscle mass size.