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Recursive digital filter for fast visual evoked potential estimation and classification

Palaniappan, Ramaswamy, Raveendran, P. (2001) Recursive digital filter for fast visual evoked potential estimation and classification. Electronics Letters, 37 (15). pp. 990-992. ISSN 0013-5194. (doi:10.1049/el:20010640) (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/10.1049/el:20010640

Abstract

Generally, visual evoked potential (VEP) estimation requires power spectrum computation. Here VEP is estimated using a recursive digital filter, which is faster and simpler to design. The method assumes VEP can be represented by a 40 Hz spectrum and the filter extracts a 40 Hz signal in the time domain, circumventing the normal procedure of power spectrum computation the normal procedure of power spectrum computation the normal procedure of power spectrum computation. Experimental results validate the method for discriminating alcoholics from control subjects.

Item Type: Article
DOI/Identification number: 10.1049/el:20010640
Additional information: Unmapped bibliographic data: LA - English [Field not mapped to EPrints] J2 - Electron. Lett. [Field not mapped to EPrints] AD - Electrical Department, Engineering Faculty, University Malaya, Kuala Lumpur 50603, Malaysia [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Article [Field not mapped to EPrints]
Uncontrolled keywords: Bandpass filters, Bandwidth, Computer simulation, Electroencephalography, Gain measurement, Neural networks, Neurophysiology, Sampled data control systems, Signal detection, Z transforms, Recursive filters, Visual evoked potential (VEP) signals, Digital filters
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 15 Dec 2018 19:08 UTC
Last Modified: 30 May 2019 08:30 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70768 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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