Boosting linear logistic regression for single trial ERP detection in rapid serial visual presentation tasks

Yonghong Huang, Deniz Erdogmus, Santosh Mathan, Misha Pavel

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

7 Scopus citations

Abstract

In this paper, we employ the AdaBoost algorithm to the linear logistic regression model to detect encephalography (EEC) signatures, called evoked response potentials of visual recognition events in a single trial. In the experiments, a large amount of images were displayed at a very high presentation rate, named rapid serial visual presentation. The EEC was recorded using 32 electrodes during the rapid image presentation. Subjects were instructed to click the mouse when they recognize a target image. The results demonstrated that the boosting method improves the detection performance compared with the base classifier by approximately 3% as measured by area under the ROC curve.

Original languageEnglish (US)
Title of host publication28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Pages3369-3372
Number of pages4
DOIs
StatePublished - Dec 1 2006
Event28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 - New York, NY, United States
Duration: Aug 30 2006Sep 3 2006

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
ISSN (Print)0589-1019

Other

Other28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
CountryUnited States
CityNew York, NY
Period8/30/069/3/06

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ASJC Scopus subject areas

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

Cite this

Huang, Y., Erdogmus, D., Mathan, S., & Pavel, M. (2006). Boosting linear logistic regression for single trial ERP detection in rapid serial visual presentation tasks. In 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 (pp. 3369-3372). [4030188] (Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings). https://doi.org/10.1109/IEMBS.2006.259370