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Ensemble averaging subspace-based approach for ERP extraction

Kamel, Nidal and Malik, Aamir and Jatoi, Munsif Ali (2013) Ensemble averaging subspace-based approach for ERP extraction. In: Proceedings of 2013 ICME International Conference on Complex Medical Engineering, May 25 - 28, Beijing, China.

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Official URL: http://dx.doi.org/10.1109/ICCME.2013.6548310

Abstract

A novel approach based on Subspace methods is proposed for extracting the Event Related Potentials (ERPs) from the background Electroencephalograph (EEG) colored noise. First, the enhancement of SNR to the neighborhood of -2 dB is achieved through the ensemble averaging of the EEG data over a limited number of trials. Then a linear estimator is used to reduce further the amount of the EEG signal in the ERPs. With this estimator the EEG colored noise is first whitened using Cholesky factorization then the eigendecomposition of the covariance matrices of prewhitened data performed and the subspace is decomposed into signal subspace and noise subspace. The components in the noise subspace are nullified and the components in the signal subspace are retained to do the improvement. The proposed algorithm is verified with simulated data and the results shows reliable performance in terms of accuracy and failure rate.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:EEG frequency band, Mean power, Sample entropy, and IQ test
Subjects:T Technology > T Technology (General)
Academic Subject One:Academic Department - Electrical And Electronics - Communications - Digital Communications - Digital Signal Processing
Departments / MOR / COE:Centre of Excellence > Center for Intelligent Signal and Imaging Research
Mission Oriented Research > Health
ID Code:10966
Deposited By: Dr Aamir Saeed Malik
Deposited On:16 Dec 2013 23:48
Last Modified:16 Dec 2013 23:48

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