Human joint motion data capture and fusion based on wearable sensors

• Published in: Autonomous intelligent systems Vol. 5; no. 1; p. 12
• Main Author: Wang, Hua
• Format: Journal Article
• Language: English
• Published: Singapore Springer Nature Singapore 01.12.2025; Springer Nature B.V; Springer
• Subjects: Accuracy; Algorithms; Artificial Intelligence; Bones; Calibration; Control and Systems Theory; Data capture; Data processing; Elbow (anatomy); Engineering; Fusion; Human mechanics; Human motion; Joints; Joints (anatomy); Kinematics; Machine Learning; Madgwick; Madgwick Wearable sensors; Motion capture; Neural networks; Older people; Original Article; Pitch (inclination); Robotics and Automation; Root-mean-square errors; Sensors; Sport science; Virtual reality; Wearable technology; Data capture; Madgwick Wearable sensors; Joints; Fusion; Madgwick

The field of human motion data capture and fusion has a broad range of potential applications and market opportunities. The capture of human motion data for wearable sensors is less costly and more convenient than other methods, but it also suffers from poor data capture accuracy and high latency. C...