Application of MEMS Sensor Data Fusion in Athlete Physical Training

The goal of this paper is to explore the application potential of MEMS (Micro-Electro-Mechanical System) sensor data fusion technology in the field of athletes' physical training. The introduction part of the article expounds the background and significance of the research, and highlights the key role of data fusion technology in enhancing training effectiveness and preventing sports injuries. In order to achieve the research purpose, this paper carefully planned the experimental scheme, selected a variety of MEMS sensors to simulate the real physical training environment, and recorded the sensor data of athletes in various training States. Then the data fusion algorithm is used to process and analyze these data in real time. The experimental results show that the data processed by MEMS sensor data fusion technology is significantly improved in accuracy and reliability compared with single sensor data. The fused data more accurately describe the athlete’s movement trajectory, speed, acceleration and other physiological parameters such as heart rate and oxygen saturation. This provides a strong basis for coaches to make training plans and adjust training load. The research conclusion points out that MEMS sensor data fusion technology shows obvious application advantages in athletes' physical training and improves the effectiveness of training.