DocumentCode :
3073418
Title :
Classification of low-level finger contraction from single channel surface EMG
Author :
Singh, Vijay Pal ; Kumar, Dinesh Kant
Author_Institution :
Bio-signal Lab, School of Electrical and Computer Engineering, RMIT University, GPO Box 2476V, Melbourne, VIC 3001 Australia
fYear :
2008
fDate :
20-25 Aug. 2008
Firstpage :
2900
Lastpage :
2903
Abstract :
This paper reports a study that has investigated a new technique to identify very low level finger flexion by the classification of single channel surface electromyogram (sEMG). The technique is based on decomposing of sEMG based on the model of transmission of motor unit action potentials (MUAP) in body tissues. This technique is relevant for identifying control commands that are often based on low level and complex muscle contraction such as finger flexion which are often a convenient way for a user to control equipment or a prosthesis device. Use of single channel is extremely important because it does not require an expert to mount the electrodes and has a further advantage in reduced cost and computational complexity. The paper reports experiments conducted on four healthy volunteer subjects with four actions and tested over 50 repetition and a high classification accuracy.
Keywords :
Electrodes; Electromyography; Feature extraction; Fingers; Low pass filters; Muscles; Prosthetics; Shape; Signal processing; Signal to noise ratio; Action Potentials; Artificial Intelligence; Electromyography; Equipment Design; Female; Fingers; Humans; Male; Muscle Contraction; Neural Networks (Computer); Pattern Recognition, Automated; Reproducibility of Results; Signal Processing, Computer-Assisted; Software; User-Computer Interface;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
Conference_Location :
Vancouver, BC
ISSN :
1557-170X
Print_ISBN :
978-1-4244-1814-5
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2008.4649809
Filename :
4649809
Link To Document :
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