Classification of Motion Types and Loads base on Human Motion Measurement
Atsushi Ito, Ryuzo Baba, Wataru YAMAZAKI, Ming Ding, Masahiro Yoshikawa, Jun Takamatsu, Tsukasa Ogasawara · The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) · 2016
In this paper, we propose a method to recognize the type and load of a measured human motion motion. The operation type can be classified using K-means and the Dynamic Time Warping method. For each type of motion, the apparent load of the motion can also be recognized by calculating the difference of the absolute sum of the angular acceleration vectors. In an experiment, we measured several types of motion to manipulate a box with three different weights. The motion type and the load can be recognized correctly with recognition rate of 83.3% and 89.6%.