i-manager Publications

Analysis of System Performances in Recovery of EEG Signals from Ocular Artifacts

B. Krishna Kumar*, K.V.S.V.R. Prasad**, K. Kishan Rao***, J. Sheshagiri Babu****

*-**-*** Professor, Jyothismathi College of Engineering and Technology, Turkaplly, Hyderabad, A.P.

**** Assistant Professor, KITS, Warangal, A.P.

Periodicity:May - July'2011
DOI : https://doi.org/10.26634/jfet.6.4.1484

Abstract

Electroencephalogram (EEG) is used for the analysis of brain signals obtained from various electrodes placed across the scalp at specific positions. The collected signals from brain are often contaminated with Ocular Artifacts (OAs), EKG and EMG artifacts. In this paper a novel technique is used for the removal of ocular artifacts using FastICA algorithm which decomposes the EEG signals into independent components then an LMS (Least Mean Squares) based adaptive algorithm is applied to the independent components so as to get the original EEG signals. In the first step, independent basis functions attributed to OA are computed using FastICA algorithm. In the second step we arrive ocular artifact free EEG signal efficiently comparative to FastICA. In this paper, based on some parameters like Root Mean Square Deviation (RMSD) and Root Mean Square Variance (RMSV) we can say that the EEG signal obtained after second step is better than after the first.

Keywords

EEG, Electrooculogram, Adaptive Filters, Artifact Rejection, Fast Independent Component Analysis.

How to Cite this Article?

Kumar, B. K. ,Prasad. K. V. S .V. R , Rao , K. K., and Babu, J. S. (2011). Analysis Of System Performances In Recovery Of EEG Signals From Ocular Artifacts. i-manager’s Journal on Future Engineering and Technology, 6(4), 27-31. https://doi.org/10.26634/jfet.6.4.1484

References

[1]. Rangaraj M, Rangayyan. (2002). ENEL 563 Biomedical signal analysis, IEEE/Wiley, New York, NY.

[2]. Comon, P. (1994). Independent component analysis, a new concept? Signal processing. 36, 287-314.

[3]. Bell, A.J., and Sejnowski, T.J. (1995). An information –maximization approach to blind separation and blind deconvolution. Neural Computation, MIT Press.7, 1129- 1159.

[4]. Making, S., Bell, A.J., Jung, T-P., and Sejnowski, T.J.,(1996). Independent Component Analysis of Electroencephalgraph-icData. Advance in Neural Information Processing Systems 8, MIT press, Cambridge MA.145-151.

[5]. Lee, T-W. (1998). Independent Component Analysis. Theory and Applications. Kluwer Academic publishers Hingham, M A, USA.

[6]. Hyvarinen, A., and Oja, E. (2000). Independent Component Analysis: Algorithms and applications. Neural Networks.13(2000), 411-430.

[7]. Vigario, R., Sarela, J., Jousmaki, V., Hamlainen, M., and Oja, E. (2000). Independent Component approch to the analysis of EEG and MEG recordings. trans. Biomed. eng. 47, 589-593.

[8]. Qiao Xiaoyan, Li Douzhe, Dong Youer. A paper, (2009). Fifth International conference on Natural computation”P300 Feature Extraction Based on Parametric Model and FastICA Algorithm”.

[9]. FC Chang, CK Chang, KY Chi, YD Lin. A paper “Evaluation Measures for Adaptive PLI Filters in ECG Signal Processing”.

[10]. Anderson, M.P.; and Woessner, W.W. (1992). Applied Groundwater Modeling: Simulation of Flow and Advective Transport (2nd Edition ed.). Academic Press.

[11]. N.P. Castellanos and V.A. Makrov, “Recovering EEG brain signals: Artifact supression with wavelet enhanced independent component analysis”, Journals of Neuroscience Methods, vol.158, pp. 300-312, 2006.

[12]. Emmanuel C. Ifeachor, and Barrrie W. Jervis. “Digital Signal Processing, A Practical approach, 2nd edition.

If you have access to this article please login to view the article or kindly login to purchase the article

Single Article

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Online	15	15

ADD TO CART

Options for accessing this content:

If you would like institutional access to this content, please recommend the title to your librarian.
If you already have i-manager's user account: Login above and proceed to purchase the article.
New Users: Please register, then proceed to purchase the article.