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Author Favieiro, G.W. ♦ Balbinot, A.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2011
Language English
Subject Domain (in DDC) Technology ♦ Medicine & health ♦ Engineering & allied operations
Subject Keyword Accuracy ♦ Electrodes ♦ Muscles ♦ Wrist ♦ Prosthetics ♦ Pattern recognition ♦ Artificial neural networks
Abstract The myoelectric signal is a sign of control of the human body that contains the information of the user's intent to contract a muscle and, therefore, make a move. Studies shows that the Amputees are able to generate standardized myoelectric signals repeatedly before of the intention to perform a certain movement. This paper presents a study that investigates the use of forearm surface electromyography (sEMG) signals for classification of five distinguish movements of the arm using just three pairs of surface electrodes located in strategic places. The classification is done by an adaptive neuro-fuzzy inference system (ANFIS) to process signal features to recognize performed movements. The average accuracy reached for the classification of five motion classes was 86–98% for three subjects.
Description Author affiliation: Department of Electrical Engineering (Laboratory IEE - PPGEE), Federal University of Rio Grande do Sul (UFRGS), Av. Osvaldo Aranha, 103 - 206, Zipcode: 90035190, Porto Alegre, RS, Brazil (Favieiro, G.W.) || Department of Electrical Engineering (DELET - Laboratory IEE - PPGEE), Federal University of Rio Grande do Sul (UFRGS), Av. Osvaldo Aranha, 103 - 206, Zipcode: 90035190, Porto Alegre, RS, Brazil (Balbinot, A.)
ISBN 9781424441211
ISSN 1557170X
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2011-08-30
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781457715891
Size (in Bytes) 728.00 kB
Page Count 4
Starting Page 7888
Ending Page 7891


Source: IEEE Xplore Digital Library