Electromyography (EMG)-signal based fuzzy-neuro control of a 3 degrees of freedom (3DOF) exoskeleton robot for human upper-limb motion assist

R. A.R.C. Gopura, Kazuo Kiguchi

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

An electromyography (EMG) signal based fuzzyneuro control method is proposed in this paper for a human upper-limb motion assist exoskeleton robot. The upper-limb exoskeleton robot (named W-EXOS) assists the motions of human forearm pronation/supination, wrist flexion/extension and ulnar/radial deviation. The paper presents the EMG signal based fuzzy-neuro control method with multiple fuzzy-neuro controllers and the adaptation method of the controllers. The skin surface EMG signals of muscles in the forearm of the exoskeleton user and the hand force/forearm torque measured from the sensors of the exoskeleton robot 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 muscle activation levels change in accordance with the angles of motions. The control method is able to adapt in accordance with the changing EMG signal levels of different users. Experiments have been performed to evaluate the proposed control method.

Original languageEnglish
Pages (from-to)241-248
Number of pages8
JournalJournal of the National Science Foundation of Sri Lanka
Volume37
Issue number4
DOIs
Publication statusPublished - Dec 2009

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Electromyography
Degrees of freedom (mechanics)
Robots
Controllers
Muscle
Fuzzy control
Exoskeleton (Robotics)
Skin
Torque
Chemical activation
Neural networks
Sensors

All Science Journal Classification (ASJC) codes

  • General

Cite this

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abstract = "An electromyography (EMG) signal based fuzzyneuro control method is proposed in this paper for a human upper-limb motion assist exoskeleton robot. The upper-limb exoskeleton robot (named W-EXOS) assists the motions of human forearm pronation/supination, wrist flexion/extension and ulnar/radial deviation. The paper presents the EMG signal based fuzzy-neuro control method with multiple fuzzy-neuro controllers and the adaptation method of the controllers. The skin surface EMG signals of muscles in the forearm of the exoskeleton user and the hand force/forearm torque measured from the sensors of the exoskeleton robot 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 muscle activation levels change in accordance with the angles of motions. The control method is able to adapt in accordance with the changing EMG signal levels of different users. Experiments have been performed to evaluate the proposed control method.",
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