Shoulder Motion Detection Algorithm Based on MPU6050 Sensor and XGBoost Model

Abstract

The shoulder joint has the most excellent range of motion in human body, which has the large range of motion ability but has poor stability. To help adjust for this instability, the rotator cuff muscles, ligaments, tendons, and the glenoid labrum should be relied on. In order to precisely evaluate the health status or mobility of the shoulder, a shoulder motion detection algorithm based on the MPU6050 motion sensor and XGBoost model is proposed in this paper. As a result, the proposed algorithm can obtain good results with accuracy of 94% and accuracy of 93%.