Artifact rejection for improving the performance of evoked potential neural network classifiers

Lalit Gupta, Dennis L. Molfese, Ravi Tammana, Mark McAvoy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper is aimed at improving, through artifact rejection, the performance of neural network evoked potential (EP) classifiers designed to detect match/mismatch conditions. A cluster analysis approach is formulated to identify artifacts that occur in the signals used for training the neural network classifiers. The clustering based artifact detection algorithm uses a distance measure resulting from a nonlinear alignment procedure designed to optimally align EP signals. Match and mismatch EPs collected for network training are clustered and the identified artifact signals are excluded from the training set. Artifacts that occur during testing are also identified and rejected by including an additional output in the neural net classifier for the artifact class. Preliminary experiments conducted show significant improvements in classification accuracy when the proposed artifact rejection methods are incorporated in the training and testing phases of a neural network EP classifier.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Pages676-686
Number of pages11
Edition2
StatePublished - Dec 1 1995
Externally publishedYes
EventOptical Engineering Midwest'95. Part 2 (of 2) - Chicago, IL, USA
Duration: May 18 1995May 19 1995

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Number2
Volume2622
ISSN (Print)0277-786X

Conference

ConferenceOptical Engineering Midwest'95. Part 2 (of 2)
CityChicago, IL, USA
Period05/18/9505/19/95

Fingerprint Dive into the research topics of 'Artifact rejection for improving the performance of evoked potential neural network classifiers'. Together they form a unique fingerprint.

  • Cite this

    Gupta, L., Molfese, D. L., Tammana, R., & McAvoy, M. (1995). Artifact rejection for improving the performance of evoked potential neural network classifiers. In Proceedings of SPIE - The International Society for Optical Engineering (2 ed., pp. 676-686). (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 2622, No. 2).