Real-time analysis of swimming training state based on adaptive filtering and swarm intelligence algorithm

Abstract

Abstract Through the sports monitoring system, can help athletes timely grasp their daily sports activities, however, the existing monitoring system still has some shortcomings. To solve this problem, we use the combination of adaptive filtering and swarm intelligence algorithm to design, and realize the real-time analysis of athletes' motion state. The filtering algorithm used in this paper is based on the filtering of the previous time, and realizes the adaptive updating of the filtering parameters of the next time without manually adjusting the parameters. The effectiveness of this method is verified by experiments, and the results are good. Because of its easy implementation and strong robustness, swarm intelligence algorithm can be used to solve a variety of complex combination problems. It can be seen from the results of system monitoring that the system can easily record and monitor their own swimming data, and develop reasonable training programs based on the data. Coaches and athletes can use this data as a basis for training and analysis, and then improve the athletes' swimming skills and competitive performance.