Skip to main content

EEG artifact reduction in VEP using 2-stage PCA and N4 analysis of alcoholics

Sharmilakanna, P., Palaniappan, Ramaswamy (2006) EEG artifact reduction in VEP using 2-stage PCA and N4 analysis of alcoholics. In: 2005 3rd International Conference on Intelligent Sensing and Information Processing. . pp. 2-7. IEEE ISBN 978-0-7803-9588-6. (doi:10.1109/ICISIP.2005.1619404) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1109/ICISIP.2005.1619404

Abstract

In this paper, repeated applications of Principal Component Analysis (PCA) are proposed to reduce background electroencephalogram (EEG) artifact from multi-channel and multi-trial Visual Evoked Potential (VEP) signals. This will allow single trial analysis of VEP signals. PCA has been used for noise reduction but the method of repeated applications of PCA is novel. In the study here, PCA was applied in 2 stages. In the first stage, PCA was applied to multi-channel VEP signals from one trial. The output VEP signals from the first stage were used in the second stage, where PCA was applied to multi-trial VEP signals from a single channel. Simulation study using emulated VEP signals contaminated with EEG artifact shows significant improvement in signal to noise ratio using the method. It was then applied to study the electrophysiological differences between alcoholic and nonalcoholic subjects using N4 parameter. Hypothesis testing using t-test showed that alcoholics had significantly weaker and slower N4 responses as compared to non-alcoholics.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/ICISIP.2005.1619404
Additional information: Unmapped bibliographic data: C7 - 1619404 [EPrints field already has value set] LA - English [Field not mapped to EPrints] J2 - Proc. - Int. Conf. Intell. Sens. Inf. Proc., ICISIP [Field not mapped to EPrints] AD - Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia [Field not mapped to EPrints] AD - Dept. of Computer Science, University of Essex, Colchester, United Kingdom [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Conference Paper [Field not mapped to EPrints] A4 - [Field not mapped to EPrints] C3 - Proceedings - 3rd International Conference on Intelligent Sensing and Information Processing, ICISIP 2005 [Field not mapped to EPrints]
Uncontrolled keywords: Alcoholism, Biomedical informatics, Blood flow, Brain modeling, Electroencephalography, Multiple sclerosis, Noise reduction, Personal communication networks, Principal component analysis, Signal analysis, Biomedical signal processing, Brain models, Electroencephalography, Electrophysiology, Noise abatement, Personal communication systems, Signal analysis, Signal to noise ratio, Alcoholism, Biomedical informatics, Blood flow, Electro-encephalogram (EEG), Multiple sclerosis, Repeated application, Single-trial analysis, Visual evoked potential, Principal component analysis
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 15 Dec 2018 14:27 UTC
Last Modified: 30 May 2019 08:29 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70750 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
  • Depositors only (login required):