A quick survey of filtering techniques for surface electromyography signals

Anas Fouad Ahmed

doi:10.30574/gjeta.2022.11.3.0101

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A quick survey of filtering techniques for surface electromyography signals

Anas Fouad Ahmed ^*

Department of Electrical Engineering, College of Engineering, Al-Iraqia University, Baghdad, Iraq.

Research Article

Global Journal of Engineering and Technology Advances, 2022, 11(03), 105–110.

Article DOI: 10.30574/gjeta.2022.11.3.0101

DOI url: https://doi.org/10.30574/gjeta.2022.11.3.0101

Publication history

Received on 17 May 2022; revised on 23 June 2022; accepted on 25 June 2022

Abstract

Electromyography (EMG) represents the electrical activity of muscles, and it has a wide range of usage in biomedical and clinical tasks. During myoelectrical stimulation, the EMG signal has two sources: the meaningful electrical response of the muscles and signal noise. Technical noise (such as power line noise) and biological noise (ECG). The noises in the system must be efficiently rejected, as this will disturb the analysis of the activity of the muscle. This paper presents different types of noise that corrupt the EMG signal and the main denoising approaches for minimizing the noise effect.

Keywords

EMG; Artifact; Denoising; Adaptive Filtering; NLM; DWT and MSE

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How to cite this article

Anas Fouad Ahmed. A quick survey of filtering techniques for surface electromyography signals. Global Journal of Engineering and Technology Advances, 2022, 11(3), 105-110. Article DOI: https://doi.org/10.30574/gjeta.2022.11.3.0101

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