This paper describes a wearable master device for people with a spinal injury who can move their neck and shoulders but cannot move their leg 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 light weight, small, and easily attached to cloth. Therefore, optical fiber curvatures 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.
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 wear-
able 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.