Evaluation of the effects of the body on athletes' emotions and motivational behaviors from the perspective of big data public health.

An analysis was conducted on the impact of the body on athletes' emotions and motivation from the perspective of Public Health (PH). PSO-KNN (Particle Swarm Optimization-K-Nearest Neighbor) algorithm and PSO-SVM algorithm (Particle Swarm Optimization-Support Vector Machine) were obtained by combining Particle Swarm Optimization (PSO), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM), and then the recognition rates of the two algorithms were compared. When comparing the PSO-KNN algorithm and PSO-SVM algorithm on baseline removed and baseline not removed, the average recognition rates of PSO-KNN algorithm and PSO-SVM algorithm under emotional state were 56.66 and 54.75%, respectively. The average recognition rates of PSO-KNN algorithm and PSO-SVM algorithm with baseline removal under tension were 53.16 and 50.58%, respectively. The algorithm that removes the baseline is better than the algorithm that does not remove the baseline, and the PSO-KNN algorithm is better than the PSO-SVM algorithm.