Influence of Visual-Inertial Sensor-to-Segment Calibration on Upper Limb Joint Angles Estimation From Multiple Inverse Kinematics Methods

This study aims to explore the potential for accurately estimating joint angles during upper limb rehabilitation tasks with different calibration procedures, inverse kinematics methods and measurement modalities. Affordable embedded visual-inertial measurement units offer a promising alternative to the costly and cumbersome gold standard marker-based optical motion capture systems. However, affordability comes with inherent sensors inaccuracies. Hence, prior to their application in a real clinical setting, it is important to demonstrate their ability for accurate joint angle estimation. Discrepancies in joint angles arise due to the inaccuracies of different sensing modalities but also to sensor-to-segment calibration procedures that significantly alter the joint offsets. Therefore, in this paper, the impact of functional and anatomical calibration procedures on joint angle estimation was compared among seven healthy young volunteers. When the same calibration procedures were applied with visual-inertial measurement units and optical motion capture systems data, a relatively small root mean square error of 7.9 deg and correlation coefficients exceeding 0.86 were observed. When different calibration procedures were applied with visual-inertial measurement units and optical motion capture systems data, higher root mean square superior to 10 deg were observed, highlighting the importance of consistency with the reference set when assessing accuracy. Furthermore, our analysis shows the benefit of using multi-body inverse kinematics procedure over treating inverse kinematics separately for each segment when dealing with inaccurate visual-inertial measurement units data. Note to Practitioners—This study addresses the practical challenge of accurately estimating upper limb joint angles in rehabilitation, using affordable Visual-Inertial Measurement Units (VIMUs) and cameras. The key finding for practitioners is the importance of consistent calibration procedures, either anatomical or functional, across both VIMUs and standard reference systems. This consistency significantly improves measurement accuracy, essential for effective rehabilitation assessment and planning. We also demonstrate that multi-body inverse kinematics (IK) methods are more reliable than single-body IK when using data from low-cost sensors. Multi-body IK better handles inaccuracies typical of affordable devices, making it a more suitable choice for clinical applications. While our results are promising, they are based on controlled conditions and do not encompass whole-body movements. Future research should focus on extending these findings to more diverse and challenging clinical scenarios, ensuring the practical applicability of this cost-effective technology in real-world rehabilitation settings.