Spatio-temporal modeling for dense array ERP classification

Srinivas Kota, Lalit Gupta, Dennis Molfese, Ravi Vaidyanathan

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

Abstract

A new strategy is introduced to exploit the enhanced spatial resolution offered by dense electrode arrays and to solve the dimensionality problem that plagues the design and evaluation of practical dense array event-related potential (ERP) classifiers. A spatiotemporal model is introduced to observe the dense array ERP amplitude variations across channels and time, simultaneously. Dimensionality reduction is achieved by selecting elements of the spatio-temporal arrays which differ in their probability distributions across the brain activity classes. Each selected spatio-temporal element is classified using an univariate Gaussian classifier and the resulting decisions are fused into a decision fusion vector which is classified using a discrete Bayes vector classifier. Using ERPs from a Stroop color test, it is shown that the performance improves significantly when the strategy is applied to normalized spatio-temporal ERP arrays. The main advantage of the new strategy is that it is not constrained by the dimensionality of the ERP vector. Consequently, it can be used to design ERP classifiers specialized for individual test subjects without having to collect a large number of ERPs from groups of subjects in order to solve the dimensionality problem.

Original languageEnglish (US)
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
PublisherIEEE Computer Society
Pages2091-2094
Number of pages4
ISBN (Print)9781424418152
DOIs
StatePublished - 2008
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: Aug 20 2008Aug 25 2008

Publication series

NameProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

Conference

Conference30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
CountryCanada
CityVancouver, BC
Period8/20/088/25/08

Keywords

  • Decision fusion
  • Dense arrays
  • Dimensionality reduction
  • Event-related potentials
  • Spatio-temporal modeling

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Fingerprint Dive into the research topics of 'Spatio-temporal modeling for dense array ERP classification'. Together they form a unique fingerprint.

  • Cite this

    Kota, S., Gupta, L., Molfese, D., & Vaidyanathan, R. (2008). Spatio-temporal modeling for dense array ERP classification. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 (pp. 2091-2094). [4649605] (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"). IEEE Computer Society. https://doi.org/10.1109/iembs.2008.4649605