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: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-04-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147720914262 |
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| _version_ | 1832547316787052544 |
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| author | Chu Rouxia Chen Xiaodong Tao Shifang Yang Donghai |
| author_facet | Chu Rouxia Chen Xiaodong Tao Shifang Yang Donghai |
| author_sort | Chu Rouxia |
| collection | DOAJ |
| 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. |
| format | Article |
| id | doaj-art-be385df82b7f4931966dd56014dd192c |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2020-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-be385df82b7f4931966dd56014dd192c2025-02-03T06:45:21ZengWileyInternational 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 |
| 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 |
| title | 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_short | 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 |
| url | https://doi.org/10.1177/1550147720914262 |
| work_keys_str_mv | AT churouxia researchoninversesimulationofphysicaltrainingprocessbasedonwirelesssensornetwork AT chenxiaodong researchoninversesimulationofphysicaltrainingprocessbasedonwirelesssensornetwork AT taoshifang researchoninversesimulationofphysicaltrainingprocessbasedonwirelesssensornetwork AT yangdonghai researchoninversesimulationofphysicaltrainingprocessbasedonwirelesssensornetwork |