Validation of a Commercially Available IMU-Based System Against an Optoelectronic System for Full-Body Motor Tasks

Highlights: What are the main findings? The IMU-based system demonstrated high concurrent validity with a gold-standard optoelectronic motion capture system across a wide variety of full-body tasks. The IMU-based system achieved strong correlations (r ≥ 0.77), low RMSE values (generally < 7°), and negligible systematic biases (≤3.9°) compared to the optical reference. What are the implications of the main findings? The tested IMU-based system provides clinically acceptable range-of-motion estimates and can serve as a reliable alternative to laboratory-based motion analysis tools. Its portability and ease of use make it particularly suited for in-clinic assessments and home-based rehabilitation programs, supporting remote patient monitoring. Inertial measurement units (IMUs) have gained popularity as portable and cost-effective alternatives to optoelectronic motion capture systems for assessing joint kinematics. This study aimed to validate a commercially available multi-sensor IMU-based system against a laboratory-grade motion capture system across lower limb, trunk, and upper limb movements. Fifteen healthy participants performed a battery of single- and multi-joint tasks while motion data were simultaneously recorded by both systems. Range of motion (ROM) values were extracted from the two systems and compared. The IMU-based system demonstrated high concurrent validity, with non-significant differences in most tasks, root mean square error values generally below 7°, percentage of similarity greater than 97%, and strong correlations (r ≥ 0.77) with the reference system. Systematic biases were trivial (≤3.9°), and limits of agreement remained within clinically acceptable thresholds. The findings indicate that the tested IMU-based system provides ROM estimates statistically and clinically comparable to those obtained with optical reference systems. Given its portability, ease of use, and affordability, the IMU-based system presents a promising solution for motion analysis in both clinical and remote rehabilitation contexts, although future research should extend validation to pathological populations and longer monitoring periods.