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Minimization of EOG artefacts from corrupted EEG signals using a neural network approach

Sadasivan, PK and Dutt, Narayana D (1994) Minimization of EOG artefacts from corrupted EEG signals using a neural network approach. In: Computers in Biology and Medicine, 24 (6). pp. 441-449.

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In this paper, we propose a neural network (NN) approach to the enhancement of EEG signals in the presence of EOG artefacts. We recast the EEG enhancement problem into the optimization framework by developing an appropriate cost function. The cost function is nothing but the energy in the enhanced EEG signal obtained through a nonlinear filter formulation, unlike the conventionally-used linear filter formulation. The minimization property of feedback-type neural networks is exploited to solve this problem. An analysis has been performed to characterize the stationary points of the suggested energy function. The hardware set-up of the developed neural network has also been derived. The optimum nonlinear filter coefficients obtained from this minimization algorithm are used to estimate the EOG artefact which is then subtracted from the corrupted EEG signal, sample by sample, to get the artefact minimized signal. The time plots as the LP spectrum show that the proposed method is very effective. Thus the power and efficacy of the NN approach have been exploited for the purpose of minimizing EOG artefacts from corrupted EEG signals.

Item Type: Journal Article
Publication: Computers in Biology and Medicine
Publisher: Elsevier
Additional Information: The copyright belongs to Elsevier.
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 17 Jun 2006
Last Modified: 19 Sep 2010 04:29
URI: http://eprints.iisc.ac.in/id/eprint/7654

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