NDLI: Identification of Contaminant Type in Surface Electromyography (EMG) Signals

Content Provider	IEEE Xplore Digital Library
Author	McCool, P. Fraser, G.D. Chan, A.D.C. Petropoulakis, L. Soraghan, J.J.
Copyright Year	2001
Abstract	The ability to recognize various forms of contaminants in surface electromyography (EMG) signals and to ascertain the overall quality of such signals is important in many EMG-enabled rehabilitation systems. In this paper, new methods for the automatic identification of commonly occurring contaminant types in surface EMG signals are presented. Such methods are advantageous because the contaminant type is typically not known in advance. The presented approach uses support vector machines as the main classification system. Both simulated and real EMG signals are used to assess the performance of the methods. The contaminants considered include: 1) electrocardiogram interference; 2) motion artifact; 3) power line interference; 4) amplifier saturation; and 5) additive white Gaussian noise. Results show that the contaminants can readily be distinguished at lower signal to noise ratios, with a growing degree of confusion at higher signal to noise ratios, where their effects on signal quality are less significant.
Sponsorship	IEEE Engineering in Medicine and Biology Society
Page Count	10
File Size	1997492
Starting Page	774
Ending Page	783
File Format	PDF
ISSN	15344320
Volume Number	22
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electromyography Signal to noise ratio Electrocardiography Interference Muscles Contamination Support vector machines prostheses Biosignal quality analysis classification electromyography (EMG) myoelectric signals
Content Type	Text
Resource Type	Article
Subject	Neuroscience Rehabilitation Internal Medicine Biomedical Engineering Computer Science Applications

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