Kinematic Analysis of Trajectory Dimension-Dependent Sensorimotor Control in Arm Tracking

Abstract

This paper aims to examine how the trajectory dimension influences sensorimotor control during arm tracking. We designed three trajectories with different dimensions in a three-dimensional (3D) immersive virtual reality environment and instructed the subjects to control a virtual hand to follow a cubic target that moved along the designed trajectories. The position of the virtual hand was determined by the position of the actual hand captured with a high-resolution 3D motion capture system in real time. Five kinematic measures were calculated: the root mean square error (RMSE), the standard deviation of the speed (speedsd), the magnitude of the jerk (Jerkm), the integral of the speed power spectrum (IVPS), and the 3D fuzzy approximate entropy (fApEn3D). All the kinematic measures increased significantly with increasing trajectory dimensions, except for the IVPS between the 1D and 2D conditions and the fApEn3D between the 2D and 3D conditions. The increase in time-domain parameters (i.e., RMSE, speedsd, and Jerkm) showed degradation in accuracy, energy efficiency, and multijoint coordination, respectively, in the higher dimensions. An increase in the frequency-domain measure (i.e., IVPS) in higher dimensional condition reflected an increase of visual feedback-related intermittency in manual control when increasing the trajectory dimension. The larger nonlinear fApEn3D values in the 2D and 3D conditions might have been due to the higher level neuromotor noise and increased sensory inputs. The selected parameters could provide a comprehensive method for evaluating motor performance from different perspectives. The findings in this paper shed light on the underlying sensorimotor control that is caused by the trajectory dimension in arm tracking tasks.