DocumentCode :
1786105
Title :
Identification of low level sEMG signals for individual finger prosthesis
Author :
Villarejo, John J. ; Costa, R.M. ; Bastos, Teodiano ; Frizera, Anselmo
Author_Institution :
Electr. Eng. Dept., Univ. Fed. do Espirito Santo, Vitoria, Brazil
fYear :
2014
fDate :
26-28 May 2014
Firstpage :
1
Lastpage :
6
Abstract :
This research reports the identification of motor tasks in a human hand from weak myoelectric signals, aimed to control a prosthesis with individual finger flexion and wrist and grasps movements. The gestures were evaluated in two groups, independently. Four channel sEMG signals were captured on the forearm from able-body and amputees volunteers, taking into account low level contraction. Linear and non-linear parameters were extracted based on time and frequency domain and Detrended Fluctuation Analysis (DFA), to represent EMG patterns. The average classification accuracies were computed using Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) to evaluate the results. Confusion matrix from some experiments show the success rate identifying the gestures.
Keywords :
electromyography; frequency-domain analysis; medical signal detection; medical signal processing; prosthetics; signal classification; support vector machines; time-domain analysis; DFA; LDA; SVM; amputees; detrended fluctuation analysis; forearm; four channel sEMG signals; frequency domain analysis; grasp movements; human hand; individual finger flexion; individual finger prosthesis; linear discriminant analysis; low level contraction; low level sEMG signal identification; motor task identification; nonlinear parameter extraction; prosthetic control; support vector machine; time domain analysis; weak myoelectric signals; wrist movements; Electrodes; Electromyography; Muscles; Support vector machines; Thumb; Wrist; fractal analysis; hand prostheses; low level contraction; myoelectric control; sEMG;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living (BRC), 5th ISSNIP-IEEE
Conference_Location :
Salvador
Print_ISBN :
978-1-4799-5688-3
Type :
conf
DOI :
10.1109/BRC.2014.6880991
Filename :
6880991
Link To Document :
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