Denoising and Analysis of EMG Signal using Wavelet Transform

Denoising and Analysis of EMG Signal using Wavelet Transform

Iffat Ara

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Pabna University of Science and Technology

Denoising and Analysis of EMG Signal using Wavelet Transform

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C3287

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Abstract

EMG is the recording of the electrical activity produced within the muscle fibers. Measurement of EMG signal is corrupted by additive noise whose signal-to-noise ratio (SNR) varies. Feature extraction is an important step for EMG classification. Time domain and frequency domain parameters were chosen as representative features for EMG signals. In this thesis, the Wavelet transform and wavelet coefficients have adopted to represent the EMG signals. Wavelet transform (WT) has been applied also in this research for the analysis of the surface electromyography signal (SEMG). The properties of wavelet transform turned out to be suitable for nonstationary EMG signals. Also Spectrum analysis has been applied to various types of EMG signal.

References

7 Cites in Article

Reference Format

Z Mohammed,Abbas Al-Faiz,Miry (2012). Artificial Human Arm Driven by EMG Signal.
E Criswell (2010). Cram's "introduction to surface electromyography.
K Englehart (1999). Classification of the myoelectric signal using time-frequency based representations.
Ingrid Daubechies (1992). Ten Lectures on Wavelets.
Grap (1995). An introduction to wavelets.
Fahreddin Sadikoglu,Cemal Kavalcioglu,Berk Dagman (2018). Electromyogram (EMG) signal detection, classification of EMG signals and diagnosis of neuropathy muscle disease.
Farzaneh Akhavan Mahdavi1,Anom Siti,Mohd Ahmad,Mohammad-R Hamiruce Marhaban,Akbarzadeh Surface Electromyography Feature Extraction Based on Wavelet Transform.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Iffat Ara. 2020. \u201cDenoising and Analysis of EMG Signal using Wavelet Transform\u201d. Global Journal of Medical Research - D: Radiology, Diagnostic GJMR-D Volume 20 (GJMR Volume 20 Issue D1).

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GJMR Volume 20 Issue D1

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Journal Specifications

Crossref Journal DOI 10.17406/gjmra

Print ISSN 0975-5888

e-ISSN 2249-4618

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GJMR-D Classification NLMC Code-WN 600

Submission ReceivedDecember 12, 2019
Peer Review Double Blind
Handling Editor
Accepted January 1, 2020
Published January 15, 2020

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v1.2

Issue date

March 16, 2020

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