DocumentCode :
3256151
Title :
Pattern recognition of electromyography applied to Exoskeleton Robot
Author :
Wang, Yang ; Zhang, Xiaodong ; Zhao, Jianping ; He, Chen
Author_Institution :
Sch. of Engine & Energy, Northwestern Polytech. Univ., Xi´´an, China
Volume :
8
fYear :
2010
fDate :
16-18 Oct. 2010
Firstpage :
3802
Lastpage :
3805
Abstract :
Exoskeleton Robot is a robotic-assisted human-machine system, which can provide power to assist the movement of people. This paper aims to find a method of EMG pattern recognition used in Exoskeleton Robot. To the beginning, the EMG power spectrum ratio (PSR) is calculated as the EMG eigenvalue. Then the minimum error-based Bayes decision rule is used to determine the movement intention of human, implemented in Matlab. The research result shows that the power spectrum density rate and the minimum error-based Bayesian decision theory can recognize the EMG on the movement intention of lower extremity exoskeleton with the advantages of easy reality and fast compute by Matlab.
Keywords :
Bayes methods; decision theory; electromyography; feature extraction; human-robot interaction; medical robotics; robot vision; EMG pattern recognition; Matlab; electromyography; exoskeleton robot; minimum error based Bayesian decision theory; power spectrum ratio; robotic assisted human machine system; Bayesian methods; Electromyography; Exoskeletons; Legged locomotion; Muscles; Pattern recognition; EMG; exoskeletal robot; feature extraction; pattern recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
Type :
conf
DOI :
10.1109/CISP.2010.5646759
Filename :
5646759
Link To Document :
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