Abstract
This paper describes a wearable, master device for people with a spinal injury who can move their neck and shoulders but cannot move their legs and arms. A device that measures the movements of their neck or shoulder can help them to drive a wheelchair. The sensors of such a wearable master device must be lightweight, small, and easily attached to cloth. Therefore, optical fiber curvature sensors are used to measure the human body motion. For a previously developed wearable master device, two calibration and mapping methods with, the sensors are proposed to extract 2-DOF human shoulder motions. One is constructed with simple geometric equations. The other is constructed with a multilayered artificial neural network. The two methods are compared. Experimental results show that the wearable master device can be used effectively for a 2-DOF input device for handicapped persons. It was also shown that a subject can control a mobile robot with the wearable master device.
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