Modeling of Hand and Forearm Link using Inertial Sensors.

In this paper, we describe our hand and forearm motion measuring system using inertial sensors. Although a sensor axis is often used to measure human body motion, it is prone to attachment and offset error, and, because a hand is made of five parallel links, it is not suitable for hand measurement. Therefore, we propose a method of modeling the hand and forearm link using only sensors. To model a finger link, a compass' azimuth deviation is important because it may affect the intersection of the fingers. Therefore, before modeling, we applied correction and alternative methods using the angular velocity direction. As a result, the deviation between the sensors decreased to 1/5. During the modeling, we estimated the sensor's position vectors on the distal and next distal segments from each joint, and calculated the relationship matrices between the sensors through initial posture during estimation. We created the hand and forearm link model by combining the position vectors and relationship matrices. Comparison with optical motion capture showed that the hand shape without intersection of the fingers matched well, but there was offset because the forearm sensors deviated from the estimated positions. Although we must improve the attachment to the forearm, these methods proved effective for hand motion measurement.