Experimental Validation of Upper-Limb Arm Motion Measured by Wearable IMUs Using a Kinect-Based Reference System

Background/Objectives: Accurate and accessible assessment of upper-limb motion is essential for rehabilitation research, ergonomic evaluation, human–machine interaction, and limb exercise. This work presents a comparative evaluation of upper-limb joint angle estimation obtained from wearable inertial measurement units (IMUs) using a Kinect-based practical benchmark during synchronized data acquisition. Methods: The main variables analyzed were shoulder and elbow joint angles, together with IMU-derived acceleration and surface electromyography (sEMG) signals acquired as complementary physiological information during task execution. Ten healthy adult participants performed predefined upper-limb movements while data from both sensing modalities were recorded simultaneously. Joint angles were estimated independently from IMU and Kinect measurements and compared using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Two One-Sided Tests (TOST) equivalence analysis. Results: For upper- limb motion, IMU-derived estimates showed practical equivalence within the predefined ±10° acceptance margin with small MAE and RMSE values and significant TOST equivalence results (p < 0.001), supporting reliable proximal joint tracking under controlled conditions. Tested elbow motion exhibited large estimation error and large variability, and although the TOST analysis was significant, the equivalence interval slightly exceeded the predefined acceptance bound, indicating comparatively weak agreement between sensing modalities. The presented results should be interpreted as proof-of-concept evidence derived from a comparative benchmark rather than as definitive validation for unrestricted or clinical implementation. The synchronized acceleration and sEMG signals provided complementary temporal information regarding movement execution but were not treated as primary comparative outputs. Conclusions: These findings support the feasibility of wearable IMU-based upper-limb joint angle estimation as a proof-of-concept comparative framework rather than definitive clinical validation. The presented findings support the feasibility of the proposed IMU-based sensing approach for upper-limb joint angle estimation, particularly at the shoulder level, while also highlighting the greater complexity of elbow-related measurements. Further investigation in larger samples, more functionally diverse tasks, and broader populations is required to extend the applicability of the proposed approach.