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77020

Efficient Denoising Schemes of EEG Signals

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Last updated: 25 Dec 2024

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Abstract

This paper presents a class of noise reduction techniques for EEG signals. The noise reduction is very important for subsequent EEG processing tasks. The suggested techniques are extended from application in speech processing to application in EEG signals due to the common nature of low frequency of both types of signals. These techniques are spectral subtraction, Wiener filtering, adaptive Wiener filtering, and Discrete Wavelet Transform (DWT). A comparison between different techniques is presented. Simulation results are used to compare between the different denoising techniques.  Four metrics are used to evaluate the different denoising techniques: signal -to-noise ratio (SNR), segmental signal-to-noise ratio (SNRseg), spectral distortion (SD), and log likelihood ratio (LLR).

DOI

10.21608/mjeer.2019.77020

Keywords

EEG, denoising, Spectral Subtraction, Wiener filter, Adaptive Wiener filter, Discrete Wavelet Transform

Authors

First Name

Zeinab

Last Name

Elsherbieny

MiddleName

-

Affiliation

Department Of Electronics And Communications Menoufia University Faculty Of Electronic Engneering,Menouf

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First Name

Nagy

Last Name

Messiha

MiddleName

-

Affiliation

Department Of Electronics And Communications Menoufia University Faculty Of Electronic Engneering,Menouf

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Orcid

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First Name

Adel S.

Last Name

El-Fisawy

MiddleName

-

Affiliation

Department Of Electronics And Communications Menoufia University Faculty Of Electronic Engneering,Menouf

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First Name

Mohamed

Last Name

Rihan

MiddleName

-

Affiliation

Department Of Electronics And Communications Menoufia University Faculty Of Electronic Engneering,Menouf

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-

Orcid

-

First Name

Fathi E.

Last Name

Abd El-Samie

MiddleName

-

Affiliation

Department Of Electronics And Communications Menoufia University Faculty Of Electronic Engneering,Menouf

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Volume

28

Article Issue

ICEEM2019-Special Issue

Related Issue

9704

Issue Date

2019-12-01

Receive Date

2020-03-11

Publish Date

2019-12-01

Page Start

209

Page End

213

Print ISSN

1687-1189

Online ISSN

2682-3535

Link

https://mjeer.journals.ekb.eg/article_77020.html

Detail API

https://mjeer.journals.ekb.eg/service?article_code=77020

Order

59

Type

Original Article

Type Code

1,088

Publication Type

Journal

Publication Title

Menoufia Journal of Electronic Engineering Research

Publication Link

https://mjeer.journals.ekb.eg/

MainTitle

Efficient Denoising Schemes of EEG Signals

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Article

Created At

22 Jan 2023