A Synchronized Multi-IMU Wearable System for Tracking of Joint-Angles in Sports Motion Analysis With Reference-Based Validation and Dynamic Task Characterization

Abstract

Reliable joint-angle measurement outside laboratory environments is important for posture assessment and technique analysis in sports and rehabilitation. Yet, wearable IMU systems, despite being the most practical solution, remain constrained by drift, multisensor timing consistency, validation, and cost. This paper presents a synchronized, cost-efficient, modular IMU wearable platform and an end-to-end pipeline for joint-angle estimation tailored to high-dynamic sports motion analysis. The system combines high-rate sensing with robust local logging, a Real Time Clock-disciplined microsecond timestamping scheme for inter-node synchronization, an indirect Kalman filter-based orientation estimator followed by relative-rotation joint-angle extraction, high-pass drift mitigation, and range normalization. Reference-based validation used a standardized seated knee flexion-extension protocol, comparing IMU-derived knee trajectories against a markerless vision reference computed from YOLOv11. The proposed method reproduced the expected 14-cycle motion and achieved low normalized error. Instrumentation performance was further evaluated using a long-duration (2h 12min) rigid-body elbow hold, yielding near-zero drift ($r_{\mathrm{drift}}=1.5\times10^{-6}$ deg/min) and a practical noise-limited resolution of $0.6442^\circ$. The system was also demonstrated on a high-dynamic clean & jerk task with two participants (professional and amateur) performing five consecutive lifts. Measured elbow and knee trajectories preserved stage-dependent signatures and rapid transients for technique interpretation, while enabling expertise-level discrimination through differences in transient timing and trajectory regularity. Overall, the results support the proposed system as a practical, temporally consistent, and cost-effective wearable approach for multi-joint technique analysis in high-dynamic settings.