Robot control using electromyography (EMG) signals of the wrist | Zendy

Charles S. DaSalla | Zendy; J. Kim | Zendy; Yasuharu Koike | Zendy

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Robot control using electromyography (EMG) signals of the wrist

Author(s) -

Charles S. DaSalla,

J. Kim,

Yasuharu Koike

Publication year - 2005

Publication title -

applied bionics and biomechanics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.397

H-Index - 23

eISSN - 1754-2103

pISSN - 1176-2322

DOI - 10.1533/abbi.2004.0054

Subject(s) - wrist , electromyography , forearm , robot , artificial neural network , computer science , torque , physical medicine and rehabilitation , interface (matter) , artificial intelligence , engineering , simulation , medicine , anatomy , physics , bubble , maximum bubble pressure method , parallel computing , thermodynamics

The aim of this paper is to design a human–interface system, using EMG signals elicited by various wrist movements, to control a robot. EMG signals are normalized and based on joint torque. A three-layer neural network is used to estimate posture of the wrist and forearm from EMG signals. After training the neural network and obtaining appropriate weights, the subject was able to control the robot in real time using wrist and forearm movements

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