EMG Signal Classification for Myoelectric Teleoperating a Dexterous Robot Hand.

EMG Signal Classification for Myoelectric Teleoperating a Dexterous Robot Hand. Research Abstract Details 

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EMG Signal Classification for Myoelectric Teleoperating a Dexterous Robot Hand. Abstract Text:

J Wang,R Wang,F Li,M Jiang,D Jin,

This paper details a strategy of discriminating finger motions using surface electromyography (EMG) signals, which could be applied to teleoperating a dexterous robot hand or controlling the advanced multi-fingered myoelectric prosthesis for hand amputees. Finger motions discrimination is the key problem in this study. Thus the emphasis is put on myoelectric signal processing approaches in this paper. The EMG signal classification system was established based on the surface EMG signals from the subject's forearm. Four pairs of electrodes were attached on the subjects to acquire the signals during six types of finger motions, i.e. thumb extension, thumb flexion, index finger extension, index finger flexion, middle finger extension, and middle finger flexion. In order to distinguish these finger motions. A combination of autoregressive (AR) model and an Artificial Neural Network (ANN) was used in the system. The discrimination procedure consists of two steps. Firstly, the AR model is used to preprocess the surface EMG signals to reduce the scale of the data. These data will be imported into the myoelectric pattern classifier. Secondly the coefficients of AR model are imported into the ANN to identify the finger motions. The experimental results show that the discrimination system works with satisfaction.

EMG Signal Classification for Myoelectric Teleoperating a Dexterous Robot Hand. Publishing Authors By Initials

J Wang,R Wang,F Li,M Jiang,D Jin,

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EMG Signal Classification for Myoelectric Teleoperating a Dexterous Robot Hand. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: Conference proceedings : ... Annual International

VOLUME: 6

Page Numbers: 5931-3

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ISSN: 1557-170X

DAY: 6

MONTH: 02

YEAR: 2005

EMG Signal Classification for Myoelectric Teleoperating a Dexterous Robot Hand. Information

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LANGUAGE: eng

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Grant and Affiliation Information for EMG Signal Classification for Myoelectric Teleoperating a Dexterous Robot Hand.

AFFILIATION: Division of Intelligent and Biomechanical System, State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China.

Country: United States

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MEDLINETA: Conf Proc IEEE Eng Med Biol So

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