Application of wavelets to electromyographic signals

Redouan Rouzky; Myriam Q. Batista; Harold G. Longbotham

doi:10.1117/12.170072

15 March 1994 Application of wavelets to electromyographic signals

Redouan Rouzky, Myriam Q. Batista, Harold G. Longbotham

Proceedings Volume 2242, Wavelet Applications; (1994) https://doi.org/10.1117/12.170072
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

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.

Citation Download Citation

Redouan Rouzky, Myriam Q. Batista, and Harold G. Longbotham "Application of wavelets to electromyographic signals", Proc. SPIE 2242, Wavelet Applications, (15 March 1994); https://doi.org/10.1117/12.170072

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