Comparison of experts and non-experts in throwing darts based on optimization criteria

Acquiring skillful movements of experts is a difficult task in many fields. Since non-experts often fail to find out how to improve their skill, it is desirable to find quantitative indices of skillful movements that clarify the difference between experts and non-experts. If we find quantitative indices, we can develop an adaptive training system using the indices. In this study, we quantitatively compare dart-throwing movements between experts and non-experts based on their scores, motions, and EMG signals. First, we show that the variance of upper-limb motion trajectories of the experts is significantly smaller than that of the non-experts. Then, we show that the displacement and the variance of the shoulder of the experts are also significantly smaller than those of the non-experts. The final result is the highlight of this study. We investigated their upper-limb motions from the viewpoint of trajectory optimization. In this study, we focus on two popular optimization criteria, i.e., sum of squared jerk over a trajectory and sum of squared joint-torque change over a trajectory. We present that the sum of squared joint torques of the subjects was negatively correlated with their scores (p < 0.05), whereas the other criteria were not.

I. Introduction

Recently, throwing motions of experts and non-experts have been compared based on biological information such as motion and electromyographic (EMG) signals [1]. For example, Proximal-to-Distal segmental Sequencing (PDS) is found in both joint-angular velocities and EMG signals [2]. PDS indicates such a phenomenon that limb motions are described by successive transitions of a joint having the highest velocity and the beginning of the EMG activation of a muscle from the body trunk to the periphery. Finding PDS is attractive because it is strongly related to synergetic motor control.