Kamel, N. and Malik, A. and Jatoi, M.A. (2013) Ensemble averaging subspace-based approach for ERP extraction. In: UNSPECIFIED.
Full text not available from this repository.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. © 2013 IEEE.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Additional Information: | cited By 1; Conference of 2013 7th ICME International Conference on Complex Medical Engineering, CME 2013 ; Conference Date: 25 May 2013 Through 28 May 2013; Conference Code:98395 |
Uncontrolled Keywords: | Cholesky factorizations; Covariance matrices; Eigen decomposition; Eventrelated potential (ERPs); Generalized eigen decomposition; Reliable performance; Subspace filtering; Visual evoked potential, Biomedical engineering; Covariance matrix; Electrophysiology; Multiuser detection; Signal analysis; Signal to noise ratio; White noise, Electroencephalography |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 09 Nov 2023 15:51 |
Last Modified: | 09 Nov 2023 15:51 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/3514 |