Optical motion capture accuracy is task-dependent in assessing wrist motion

Abstract

Optical motion capture (OMC) systems are commonly used to capture in-vivo three-dimensional joint kinematics. However, the skin-based markers may not reflect the underlying bone movement, a source of error known as soft tissue artifact (STA). This study examined STA during wrist motion by evaluating the agreement between OMC and biplanar videoradiography (BVR). Nine subjects completed 7 different wrist motion tasks: doorknob rotation to capture supination and pronation, radial-ulnar deviation, flexion-extension, circumduction, hammering, and pitcher pouring. BVR and OMC captured the motion simultaneously. Wrist kinematics were quantified using helical motion parameters of rotation and translation, and Bland-Altman analysis quantified the mean difference (bias) and 95% limit of agreement (LOA). The rotational bias of doorknob pronation, a median bias of -4.9°, was significantly larger than the flexion-extension (0.7°, p < 0.05) and radial-ulnar deviation (1.8°, p < 0.01) tasks. The rotational LOA range was significantly smaller in the flexion-extension task (5.9°) compared to pitcher (11.6°, p < 0.05) and doorknob pronation (17.9°, p < 0.05) tasks. The translation bias did not differ between tasks. The translation LOA range was significantly larger in circumduction (9.8°) compared to the radial-ulnar deviation (6.3°, p < 0.05) and pitcher (3.4°, p < 0.05) tasks. While OMC technology has a wide-range of successful applications, we demonstrated it has relatively poor agreement with BVR in tracking wrist motion, and that the agreement depends on the nature and direction of wrist motion.

Keywords: Accuracy; Kinematics; Optical motion capture; Soft tissue artifact; Wrist.