Machine Vision Technology Based on Wireless Sensor Network Data Analysis for Monitoring Injury Prevention Data in Yoga Sports

Abstract

With the popularity of yoga around the world, the number of sports injuries caused by incorrect postures is also increasing. Traditional monitoring methods rely on manual observation and static data analysis, which is difficult to detect and prevent injury timely and accurately. This study aims to explore how to realize real-time monitoring and analysis of yoga practitioners' movement posture through wireless sensor network (WSN) combined with machine vision technology, so as to effectively prevent sports injuries. In this paper, a monitoring system based on WSN is constructed, which arranges sensor nodes in the key parts (such as joints) of exercisers to collect real-time motion data. Combined with machine vision technology, the collected data is processed and analyzed to identify incorrect motion posture. The system transmits data through wireless network, uses algorithms to analyze the attitude, and provides real-time feedback. The experimental results show that the WSN based monitoring system can efficiently collect the movement data of yoga practitioners, and accurately identify the incorrect posture through machine vision technology. Compared with the traditional method, this system significantly improves the timeliness and accuracy of monitoring.