Implementation of Complete Ensemble Empirical Mode Decomposition to Analyze EOG Signals for Eye Blink Detection

Implementation of Complete Ensemble Empirical Mode Decomposition to Analyze EOG Signals for Eye Blink Detection

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Implementation of Complete Ensemble Empirical Mode Decomposition to Analyze EOG Signals for Eye Blink Detection

Md. Sakib Galib Sourav Khulna University of Engineering & Technology

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Abstract

This paper reports on application of Complete Ensemble Empirical Mode Decomposition (CEEMD) technique to pre-process Electro-Oculogram (EOG) signals before eye blink detection technique is implemented. EOG is a non-stationary signal which is affected by different kinds of interferences. During the time of recording EOG signal gets contaminated by Electromyography (EMG) signal. In this paper CEEMD is used to decompose the EOG signal into several intrinsic mode functions (IMFs). After thresholding each IMF the signal is reconstructed using all of the IMFs. The resulting denoised signal is then used to detect eye blink

Implementation of Complete Ensemble Empirical Mode Decomposition to Analyze EOG Signals for Eye Blink Detection

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Md. Sakib Galib Sourav Khulna University of Engineering & Technology

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How to Cite

Md. Sakib Galib Sourav. 2016. “. Global Journal of Research in Engineering – F: Electrical & Electronic GJRE-F Volume 16 (GJRE Volume 16 Issue F3): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

GJRE Volume 16 Issue F3
Pg. 1- 4

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Classification

GJRE-F Classification: FOR Code: 090699

Submission Received December 13, 2015
Accepted January 2, 2016
Published January 15, 2016

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Article Matrices

Total Score: 101

Country: Bangladesh

Subject: Global Journal of Research in Engineering - F: Electrical & Electronic

Authors: Md. Sakib Galib Sourav (PhD/Dr. count: 0)

View Count (all-time): 179

Total Views (Real + Logic): 3788

Total Downloads (simulated): 1929

Publish Date: 2016 03, Tue

Monthly Totals (Real + Logic):

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Total Views: 3788

Total Downloads: 1929

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