Open AccessAn auxiliary system for rehabilitation training
Author(s) -
Xuehua Liu,
Zhenkun Lin,
Zhencheng Lin
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1920/1/012078
Subject(s) - squatting position , rehabilitation , squat , training (meteorology) , computer science , cloud computing , training system , action (physics) , human–computer interaction , artificial intelligence , simulation , embedded system , physical medicine and rehabilitation , operating system , psychology , physical therapy , economics , medicine , physics , quantum mechanics , meteorology , economic growth , neuroscience
In this paper, aiming at the problem of sports injury in squatting, the development of squatting training assistant system based on MPU9250 is proposed and designed. The system uses embedded technology, through the cloud architecture of recurrent neural network to analyze data, realize the monitoring of squat training, return the results to the mobile APP end, realize the correction and guidance of each action, and display the user’s rehabilitation in real time. Through the system test, the results show that the system has the characteristics of stable performance, accurate detection, convenient and portable.