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Techniques for Decomposition of EMG Signals

Techniques for Decomposition of EMG Signals
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Author(s): Arun Kumar Wadhwani (MITS, India) and Sulochana Wadhwani (MITS, India)
Copyright: 2011
Pages: 11
Source title: Clinical Technologies: Concepts, Methodologies, Tools and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-60960-561-2.ch216

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Abstract

The information extracted from the EMG recordings is of great clinical importance and is used for the diagnosis and treatment of neuromuscular disorders and to study muscle fatigue and neuromuscular control mechanism. Thus there is a necessity of efficient and effective techniques, which can clearly separate individual MUAPs from the complex EMG without loss of diagnostic information. This chapter deals with the techniques of decomposition based on statistical pattern recognition, cross-correlation, Kohonen self-organizing map and wavelet transform.

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