TY - GEN
T1 - A human forearm and wrist motion assist exoskeleton robot with EMG-based fuzzy-neuro control
AU - Gopura, R. A.R.C.
AU - Kiguchi, Kazuo
PY - 2008/12/1
Y1 - 2008/12/1
N2 - In this paper, an EMG-based fuzzy-neuro control method is proposed for a three degree of freedom (3 DOF) human forearm and wrist motion assist exoskeleton robot (W-EXOS). The W-EXOS assists human forearm pronation/supination motion, wrist flexion/extension motion and ulnar/radial deviation. The paper presents the EMG-based fuzzyneuro control method with multiple fuzzy-neuro controllers and the adaptation method of controllers. The skin surface electromyography (EMG) signals of muscles in forearm of the exoskeleton users' and the hand force/forearm torque are used as input information for the controllers. Fuzzy-neuro control method, which is a combination of flexible fuzzy control and adaptive neural network control, has been applied to realize the natural and flexible motion assist. In the control method, multiple fuzzy-neuro controllers are applied, since the muscles activation levels change in accordance with the angles of motions. The control method is able to adapt according the changing EMG signal levels of different users. Experiments have been performed to evaluate the proposed EMG-based fuzzy-neuro control method.
AB - In this paper, an EMG-based fuzzy-neuro control method is proposed for a three degree of freedom (3 DOF) human forearm and wrist motion assist exoskeleton robot (W-EXOS). The W-EXOS assists human forearm pronation/supination motion, wrist flexion/extension motion and ulnar/radial deviation. The paper presents the EMG-based fuzzyneuro control method with multiple fuzzy-neuro controllers and the adaptation method of controllers. The skin surface electromyography (EMG) signals of muscles in forearm of the exoskeleton users' and the hand force/forearm torque are used as input information for the controllers. Fuzzy-neuro control method, which is a combination of flexible fuzzy control and adaptive neural network control, has been applied to realize the natural and flexible motion assist. In the control method, multiple fuzzy-neuro controllers are applied, since the muscles activation levels change in accordance with the angles of motions. The control method is able to adapt according the changing EMG signal levels of different users. Experiments have been performed to evaluate the proposed EMG-based fuzzy-neuro control method.
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U2 - 10.1109/BIOROB.2008.4762793
DO - 10.1109/BIOROB.2008.4762793
M3 - Conference contribution
AN - SCOPUS:63249103353
SN - 9781424428830
T3 - Proceedings of the 2nd Biennial IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2008
SP - 550
EP - 555
BT - Proceedings of the 2nd Biennial IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2008
T2 - 2nd Biennial IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2008
Y2 - 19 October 2008 through 22 October 2008
ER -