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

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Md. Sakib Galib Sourav
Md. Sakib Galib Sourav
α Khulna University of Engineering and Technology

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

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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.

References

9 Cites in Article
  1. Xiaopei Zhao Lv,Mi Wu,Li (2008). Implementation of the EOG-based Human Computer Interface System.
  2. M Reddy,A Sammaiah,B Narsimha,K Rao (2011). Analysis of EOG Signals Using Empirical Mode Decomposition for Eye Blink Detection.
  3. Z Shen,Q Wang,Y Shen,J Jin,Y Lin (2010). Accent extraction of emotional speech based on modified ensemble empirical mode decomposition.
  4. Z Wu,N Huang (2009). Ensemble Empirical Mode Decomposition: a Noise-Assisted Data Analysis Method.
  5. Maria Torres,Marcelo Colominas,Gaston Schlotthauer,Patrick Flandrin (2011). A complete ensemble empirical mode decomposition with adaptive noise.
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  8. C Yue (2011). EOG signals in drowsiness research.
  9. Alexandre Pavlovski (2025). Towards Canada’s Transcontinental Supergrid: AC/DC Transmission Merge Solutions.

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

Md. Sakib Galib Sourav. 2016. \u201cImplementation of Complete Ensemble Empirical Mode Decomposition to Analyze EOG Signals for Eye Blink Detection\u201d. 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

Keywords
Classification
GJRE-F Classification: FOR Code: 090699
Version of record

v1.2

Issue date

March 29, 2016

Language
en
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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.

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

Md. Sakib Galib Sourav
Md. Sakib Galib Sourav Khulna University of Engineering and Technology

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