• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1541-1544
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• 1997

The rehailitation robot, one of the service robot, is the important area in the service automation. In the paper, we describe the overall configuration of KARES(KAIST Rehabilitation Engineering System), which is an intellingent rehabilitaion robotic system designed to assist the independent livelihood of the handicapped and the eldrly. KARES consists of the 6 degree of freedom robot arm mounted on a wheelchair, the controller ofr the arm, sensors to perceive environment, and user interface. Basic desired hobs in KARES are gripping the target object and moving it to the user's face for eating, drinking, or cooperation work wiht the mouth. Currently, the manual operation of the arm is available for gripping to target objects. The autonomous functionality will be ginven for the facilities of the human operator.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.1
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• pp.1-5
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• 2017

It is important to train lower limb muscle strength using a tilting table to recover the lower extremity function of hemiplegia patients. It is known that the foot deformity and poor posture of hemiplegia patients can reduce the effectiveness of lower limb rehabilitation training. In this study, we developed a sensor system that can measure the foot pressure distribution of the patients for the load control of the lower extremity during lower limb rehabilitation training and it can be substituted for conventional high-cost technologies.

• 전자공학회논문지 IE
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• v.43 no.4
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• pp.28-36
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• 2006

In this paper, an algorithm to classify the 4 motions of arm and a control system to position control the prosthesis are studied. To classify the 4 motions, we use flex sensors which is electrical resistance type sensor that can measure warp of muscle. The flex sensors are attached to the biceps brchii muscle and coracobrachialis muscle and the sensor signals are passed the sensing system. 4 motion of the forearm - flexion and extension, the pronation and supination are classified from this. Also position of forearm is measured from the classified signals. Finally, A two D.O.F prosthesis arm with RC servo-motor is designed to verify the validity of the algorithm. At this time, fuzzy controller is used to reduce the position error by rotary inertia and noise. From the experiment, the position error had occurred within about 5 degree.