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Research on inverse simulation of physical training process based on wireless sensor network

Author

Listed:
  • Chu Rouxia
  • Chen Xiaodong
  • Tao Shifang
  • Yang Donghai

Abstract

In order to improve the control ability of the human body in the process of physical training, it is necessary to carry out the inverse simulation analysis of the physical training process and establish the process control model of the physical training. The complex problem of high-dimensional spatial motion planning involved in physical training is decomposed into a series of sub-problems in low-dimensional space, and the inertial attitude parameter fusion is carried out according to the position and pose state of the human body in the end of the workspace during the process of physical training. The design of sensor node and base station in the system can realize real-time collection of motion parameters of motion collectors. The multi-dimensional control of physical training process is carried out by fuzzy constraint and inverse integral control, and the attitude parameters of human body are adjusted by means of mechanical analysis model and inertial parameter analysis method. The simulation results show that the inversion simulation control has better convergence, higher control quality, and better inverse simulation performance in the process of physical training, which can effectively guide physical training and improve the effect of physical training.

Suggested Citation

  • Chu Rouxia & Chen Xiaodong & Tao Shifang & Yang Donghai, 2020. "Research on inverse simulation of physical training process based on wireless sensor network," International Journal of Distributed Sensor Networks, , vol. 16(4), pages 15501477209, April.
  • Handle: RePEc:sae:intdis:v:16:y:2020:i:4:p:1550147720914262
    DOI: 10.1177/1550147720914262
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    1. Luobing Dong & Qiumin Guo & Weili Wu, 2019. "Speech corpora subset selection based on time-continuous utterances features," Journal of Combinatorial Optimization, Springer, vol. 37(4), pages 1237-1248, May.
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