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

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 spati...

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Main Authors: Chu Rouxia, Chen Xiaodong, Tao Shifang, Yang Donghai
Format: Article
Language:English
Published: SAGE Publishing 2020-04-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1177/1550147720914262
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spelling doaj-be385df82b7f4931966dd56014dd192c2020-11-25T03:51:43ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772020-04-011610.1177/1550147720914262Research on inverse simulation of physical training process based on wireless sensor networkChu Rouxia0Chen Xiaodong1Tao Shifang2Yang Donghai3Shanghai University of Sport, Shanghai, ChinaShanghai Pudong New District Second Children’s Sports School, Shanghai, ChinaHong Kong Federation of Trade Unions Workers’ Medical Clinic, Hong Kong, ChinaShanghai Elite Sport Training Administration Center, Shanghai, ChinaIn 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.https://doi.org/10.1177/1550147720914262
collection DOAJ
language English
format Article
sources DOAJ
author Chu Rouxia
Chen Xiaodong
Tao Shifang
Yang Donghai
spellingShingle Chu Rouxia
Chen Xiaodong
Tao Shifang
Yang Donghai
Research on inverse simulation of physical training process based on wireless sensor network
International Journal of Distributed Sensor Networks
author_facet Chu Rouxia
Chen Xiaodong
Tao Shifang
Yang Donghai
author_sort Chu Rouxia
title Research on inverse simulation of physical training process based on wireless sensor network
title_short Research on inverse simulation of physical training process based on wireless sensor network
title_full Research on inverse simulation of physical training process based on wireless sensor network
title_fullStr Research on inverse simulation of physical training process based on wireless sensor network
title_full_unstemmed Research on inverse simulation of physical training process based on wireless sensor network
title_sort research on inverse simulation of physical training process based on wireless sensor network
publisher SAGE Publishing
series International Journal of Distributed Sensor Networks
issn 1550-1477
publishDate 2020-04-01
description 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.
url https://doi.org/10.1177/1550147720914262
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AT chenxiaodong researchoninversesimulationofphysicaltrainingprocessbasedonwirelesssensornetwork
AT taoshifang researchoninversesimulationofphysicaltrainingprocessbasedonwirelesssensornetwork
AT yangdonghai researchoninversesimulationofphysicaltrainingprocessbasedonwirelesssensornetwork
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