Central-tendency estimation and nearest-estimate classification of multi-channel evoked potentials

Srinivas Kota, Phani Yarlagadda, Lalit Gupta, D. L. Molfese

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

2 Scopus citations

Abstract

By modeling evoked potentials (EPs) as random vectors in which the EP samples are random variables, a generalized strategy is introduced to determine multivariate central-tendency estimates such as the arithmetic mean, geometric mean, harmonic mean, median, tri-mean, and trimmed-mean. Additionally, a generalized strategy is introduced to develop minimum-distance classifiers based on central tendency estimates. Furthermore, procedures are developed to fuse the decisions of the nearest-estimate classifiers for multi-channel EP classification. The central-tendency estimates of real EPs are compared and it is shown that although the mathematical operations to compute the estimates are quite different, the EP estimates are similar with respect to their overall waveform shapes and latencies. It is also shown that by fusing the classifier decisions across multiple channels, the classification accuracy can be improved significantly when compared with the accuracies of individual channel classifiers.

Original languageEnglish (US)
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEngineering the Future of Biomedicine, EMBC 2009
PublisherIEEE Computer Society
Pages2575-2578
Number of pages4
ISBN (Print)9781424432967
DOIs
StatePublished - 2009
Event31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States
Duration: Sep 2 2009Sep 6 2009

Publication series

NameProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

Conference

Conference31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
CountryUnited States
CityMinneapolis, MN
Period9/2/099/6/09

Keywords

  • Central tendency estimation
  • EP averaging
  • EP classification
  • Evoked potentials

ASJC Scopus subject areas

  • Cell Biology
  • Developmental Biology
  • Biomedical Engineering
  • Medicine(all)

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    Kota, S., Yarlagadda, P., Gupta, L., & Molfese, D. L. (2009). Central-tendency estimation and nearest-estimate classification of multi-channel evoked potentials. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 (pp. 2575-2578). [5335281] (Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009). IEEE Computer Society. https://doi.org/10.1109/IEMBS.2009.5335281