Detection and biomechanical analysis of human posture embedded electronic system based on D-H matrix method

Abstract

Background: This study aims to model the kinematics of human joints using the Denavit-Hartenberg matrix method (hereinafter referred to as D-H matrix method) and combine biomechanical analysis for posture evaluation, thereby providing a more accurate and efficient detection solution. It ensures the implementation of complex calculations under low-power conditions and has broad application prospects in fields such as rehabilitation medicine, sports analysis, and virtual reality. Objective: The aim of this study is to design a sensor fusion-based embedded electronic system by integrating nine-axis sensors such as accelerometers, gyroscopes, and magnetometers. This system combines the D-H matrix method and forward kinematics for human posture detection and biomechanical analysis, to improve the system’s detection accuracy and response speed. Methods: Traditional forward kinematics and the D-H matrix method are used for kinematic modeling to enhance the accuracy and efficiency of posture calculation. Innovation: The D-H matrix method, a classical analysis technique in robotics typically used for kinematic analysis of robotic arms, is successfully applied in this study to human posture detection, breaking through traditional posture analysis methods. By utilizing the D-H matrix method to model the movement relationships between human joints, this study provides a more precise mathematical model for posture detection. By combining embedded electronic systems with biomechanical analysis to evaluate human posture, and introducing real-time monitoring of biomechanical loads from a biomechanical perspective, this study ensures that real-time human posture detection is not only efficient but also capable of performing complex calculations under low power conditions. Results: To further improve the accuracy of the sensors, this study analyzed the error characteristics of the inertial sensors and applied preprocessing algorithms to correct the errors in the signals from the magnetometer, accelerometer, and gyroscope. Combined with a high-pass and low-pass complementary filter fusion algorithm, the experiment showed that this algorithm successfully resolved the random drift and cumulative errors in the attitude angles calculated. The posture calculation system using the D-H matrix method outperforms the traditional forward kinematics method in terms of response time and root mean square error (hereinafter referred to as MSE). For instance, the response time for the right upper arm is reduced by 74.67% compared to traditional methods, while the MSE remains within a reasonable range.