A Practical Sensor-to-Segment Calibration Method for Upper Limb Inertial Motion Capture in a Clinical Setting

Abstract

Inertial sensors have the potential to be a useful clinical tool because they can facilitate human motion capture outside the research setting. A major barrier to the widespread application of inertial motion capture is the lack of accepted calibration methods for ensuring accuracy, in particular the lack of a common convention for calculating the rotational offset of the sensors, known as sensor-to-segment calibration. The purpose of this study was to develop and test a sensor-to-segment calibration method for upper limb motion capture which is practical for clinical applications.We developed a calibration method which depends mainly on the estimation of joint axes from arbitrary elbow motion, and partially on the design of custom attachment mounts to achieve physical alignment. With twenty healthy participants, we used OpenSim’s inertial sensor workflow to calculate joint kinematics, and evaluated the accuracy of the method through comparison with optical motion capture.We found the new calibration method resulted in upper limb kinematics with a median RMS error of 5–8°, and a median correlation coefficient of 0.977–0.987, which was significantly more accurate than a static pose calibration (p-value < 0.001).This work has demonstrated a method of calibration which is practical for clinical applications because it is quick to perform and does not depend on the subject’s ability to perform specific movements, or on the operator’s ability to carefully place sensors.Clinical Impact: The calibration method proposed in this work is a realistic option for the translation of inertial sensor technology into everyday clinical use.