Affiliations: Sports Institute, Henan University of Technology, Zhengzhou, Henan 450000, China | E-mail: zhouliping201407@163.com
Correspondence:
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Corresponding author: Sports Institute, Henan University of Technology, Zhengzhou, Henan 450000, China. E-mail: zhouliping201407@163.com.
Abstract: Traditional motion posture monitoring system has some problems such as time-consuming monitoring, low monitoring accuracy and poor monitoring effect. Therefore, this paper designs a real-time motion posture monitoring system based on sensor data flow. In the aspect of hardware, the whole structure of human motion posture monitoring system is designed. The mPU-92/65 six-axis motion processing sensor is selected to collect motion posture, and the module of human motion status detection is designed by MEMS sensor. In software, according to the amplitude fusion information of sensor output and correlation mining, fuzzy fusion model of motion posture data acquisition is established by using correlation component detection method, and real-time monitoring of motion posture is realized by combining sensor data flow technology. The experimental results show that when the number of iterations is 300, the motion posture monitoring accuracy of the designed system can reach 99.57%, the motion posture monitoring time is only 31 ms, and the motion posture monitoring recall rate is as high as 98.65%, indicating that the designed system can improve the motion posture monitoring effect.
Keywords: MEMS sensor, sensor data flow, detection of relevant components, motion posture, association mining
