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Proceedings Paper

Application of wavelets to electromyographic signals
Author(s): Redouan Rouzky; Myriam Q. Batista; Harold G. Longbotham
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Paper Abstract

Electromyographic (EMG) signals are pulse-based signals with the high-energy components located in the pulses, also called envelopes. These pulses contain information that is vital for EMG signal analysis. In a person with a spinal cord injury, the envelopes are cluttered with noise and are difficult to detect. In this paper, we will show that the simultaneous use of a pico filter (FatBear) and wavelets is a robust method for the detection of the signal in a cluttered environment. The FatBear, a nonarithmetic, piecewise continuous filter, can be used as a filter for pulse-width filtering, impulse rejection, and edge enhancement. The FatBear will be used as a preliminary step to eliminate the impulsive noise present in the signal. Wavelet techniques will then be applied to process the signal. As a result, we will obtain the information in the pulse interval without the noise.

Paper Details

Date Published: 15 March 1994
PDF: 8 pages
Proc. SPIE 2242, Wavelet Applications, (15 March 1994); doi: 10.1117/12.170072
Show Author Affiliations
Redouan Rouzky, Univ. of Texas/San Antonio (United States)
Myriam Q. Batista, Univ. of Texas/San Antonio (United States)
Harold G. Longbotham, Univ. of Texas/San Antonio and Conceptual Mindworks Inc. (United States)


Published in SPIE Proceedings Vol. 2242:
Wavelet Applications
Harold H. Szu, Editor(s)

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