Skip to main content
Kent Academic Repository

Single trial VEP source separation through sandwich spectral power ratio method

Andrews, S., Palaniappan, Ramaswamy, Kamel, N. (2005) Single trial VEP source separation through sandwich spectral power ratio method. In: Proceedings of the 1st International Conference on Computers, Communications, & Signal Processing. . IEEE ISBN 978-1-4244-0011-9. (doi:10.1109/CCSP.2005.4977147) (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) (KAR id:70739)

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.
Official URL:
http://dx.doi.org/10.1109/CCSP.2005.4977147

Abstract

In single trial source separation problem of VEP signals, the selection of legitimate Principal Components (PCs) is an important phenomenon. The Spectral Power Ratio (SPR) method developed by us earlier for PCA has proven to be capable of selecting only the required pes in a sophisticated manner. Our continuous enhancement has lead to the current development of the proposed method, Sandwich SPR (SSPR). The SSPR performs the reconstruction of source signal in an effective way better than the related SPR method. When this technique was applied on artificial Visual Evoked Potential (VEP) signals contaminated with background electroencephalogram (EEG), with a focus on extracting P3 parameters, it was found to be feasible shown by the resulting high values of the Signal to Noise ratio (SNR) as compared to the SPR and 2 tier SPR (SPR2) methods. Subsequently, we applied this method to study the P3 amplitude responses from a set of real EEG from Wadsworth BCI dataset obtained with target and non-target stimuli,d and found that the P3 parameters extracted through our proposed SSPR method showed higher P3 responses for the target stimuli than the both SPR and SPR2 methods, which conform to the existing knowledge on P3 responses.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/CCSP.2005.4977147
Additional information: Unmapped bibliographic data: C7 - 4977147 [EPrints field already has value set] LA - English [Field not mapped to EPrints] J2 - Int. Conf. Comput., Commun. Signal Process. Spec. Track Biomed. Eng., CCSP [Field not mapped to EPrints] AD - Faculty of Information Science and Technology, Multimedia University, Malacca, Malaysia [Field not mapped to EPrints] AD - Dept.of Computer Science, University of Essex, Colchester, United Kingdom [Field not mapped to EPrints] AD - Faculty of Engineering and Technology, Multimedia University, Malacca, Malaysia [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Conference Paper [Field not mapped to EPrints] C3 - 2005 1st International Conference on Computers, Communications and Signal Processing with Special Track on Biomedical Engineering, CCSP 2005 [Field not mapped to EPrints]
Uncontrolled keywords: Electroencephalogram, P3, Principal components, Single trial analysis, Visual Evoked Potential, Electroencephalogram, P3, Principal components, Single trial analysis, Visual Evoked Potential, Biomedical engineering, Electroencephalography, Optical sensors, Signal analysis, Signal processing, Signal to noise ratio, Surface plasmon resonance, Targets, Principal component analysis
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Palaniappan Ramaswamy
Date Deposited: 15 Dec 2018 19:57 UTC
Last Modified: 05 Nov 2024 12:33 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70739 (The current URI for this page, for reference purposes)

University of Kent Author Information

Palaniappan, Ramaswamy.

Creator's ORCID: https://orcid.org/0000-0001-5296-8396
CReDIT Contributor Roles:
  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.