Decision-level fusion of EEG and pupil features for single-trial visual detection analysis.

Published

Journal Article

Several recent studies have reported success in applying EEG-based signal analysis to achieve accurate single-trial classification of responses to visual target detection. Pupil responses are proposed as a complementary modality that can support improved accuracy of single-trial signal analysis. We develop a pupillary response feature-extraction and -selection procedure that helps to improve the classification performance of a system based only on EEG signal analysis. We apply a two-level linear classifier to obtain cognitive-task-related analysis of EEG and pupil responses. The classification results based on the two modalities are then fused at the decision level. Here, the goal is to support increased classification confidence through the inherent modality complementarities. The fusion results show significant improvement over classification performance based on a single modality.

Full Text

Duke Authors

Cited Authors

  • Qian, M; Aguilar, M; Zachery, KN; Privitera, C; Klein, S; Carney, T; Nolte, LW

Published Date

  • July 2009

Published In

Volume / Issue

  • 56 / 7

Start / End Page

  • 1929 - 1937

PubMed ID

  • 19336285

Pubmed Central ID

  • 19336285

Electronic International Standard Serial Number (EISSN)

  • 1558-2531

International Standard Serial Number (ISSN)

  • 0018-9294

Digital Object Identifier (DOI)

  • 10.1109/tbme.2009.2016670

Language

  • eng