Data Fusion Model for Muscle Proteomics in Sports Applications

Proteome is a cell, tissue, or organism to express all the floorboard of the protein; proteomics is the study of proteomics is an emerging discipline; the research on the law of occurrence of sports fatigue and its mechanism is an important and challenging subject in the field of sports medicine. Exercise-induced fatigue refers to the physiological process in which the body’s functional ability or work efficiency declines and cannot be maintained at a specific level during exercise. With the improvement of the modern competitive sports level and the increasingly fierce competition, the athletes have to bear more and more loads in sports training, and the probability of sports fatigue is also higher. Appropriate sports fatigue and reasonable recovery methods can promote the improvement of athletes’ functional level; on the contrary, excessive fatigue not only affects the training effect but may also cause various dysfunctions, which may damage the athletes’ health. Therefore, understanding the mechanism of sports fatigue is of positive significance for accelerating the elimination of sports fatigue. The purpose of this paper is to study the progress of muscle proteomics in sports. Since each athlete has individual differences, different levels of muscle function corresponding to the left lower limb will produce different EMG signals. Static experiments and random visual stimulation evaluation experiments were performed on the left lower limbs of athletes, and they were coordinated with the right lower limbs, and then the left and right lower limbs were compared with the same muscle-weighted RMS (Recipe Management System) and IEMG (Comprehensive electromyography). Experimental results show that using the statistical method of single-factor variance analysis to the same muscles in two states of RMS was analyzed, respectively, under the two states of differences between muscle electromyography IEMG were analyzed, finally, the muscle integral electrical values on the contribution rate of extent of each muscle under the two states are analyzed. For one-way ANOVA, this study defined the significance level of the difference analysis between groups as . is a small probability event, indicating that the possibility of an event occurring is very small, so it is considered that the event is unlikely to occur. A low-probability event is an event that has a low probability of occurring. Then, it is almost impossible to happen in one experiment, but it is bound to happen in many repeated experiments. With the continuous improvement of existing technologies and the emergence of more new technologies, proteomics research will make greater contributions to elucidate the mechanism of exercise on skeletal muscle remodeling and its improvement on health.