Evaluation of neck motion due to change in working velocity based on feature extraction with motion division

Abstract

In recent year, the evaluation method of human motion to clarify the usability is needed because it is a hard task to assess the subjective evaluation of usability of product and the comfort of the environment. This study aimed to analyze neck motion using feature extraction with motion division and clarify the relationship between neck motion and workability. We propose the motion division method based on the calculation of probability density function from the Gaussian distribution. The algorithm being proposed uses the analysis of the measured data by an experiment. As part of the experiment, each participant was instructed to gaze at a target while in the sitting posture. The working posture of each participant was measured to evaluate the effects of working velocity on the position of the target. The numbers of extracted feature point decreased with the decreasing working velocity. The normal working velocity condition maximized the number of extracted feature points. Moreover, participants answered the best subjective workability under normal conditions. These results show that increasing the number of extracted feature points may improve workability.