Automatic detection of critical epochs in coma-EEG using independent component analysis and higher order statistics

G. Inuso, F. La Foresta, N. Mammone, F. C. Morabito

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

Abstract

Previous works showed that the joint use of Principal Component Analysis (PCA) and Independent Component Analysis (ICA) allows to extract a few meaningful dominant components from the EEG of patients in coma. A procedure for automatic critical epoch detection might support the doctor in the long time monitoring of the patients, this is why we are headed to find a procedure able to automatically quantify how much an epoch is critical or not. In this paper we propose a procedure based on the extraction of some features from the dominant components: the entropy and the kurtosis. This feature analysis allowed us to detect some epochs that are likely to be critical and that are worth inspecting by the expert in order to assess the possible restarting of the brain activity.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages82-91
Number of pages10
Volume4234 LNCS - III
ISBN (Print)3540464840, 9783540464846
Publication statusPublished - 2006
Event13th International Conference on Neural Information Processing, ICONIP 2006 - Hong Kong, China
Duration: Oct 3 2006Oct 6 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4234 LNCS - III
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other13th International Conference on Neural Information Processing, ICONIP 2006
CountryChina
CityHong Kong
Period10/3/0610/6/06

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Inuso, G., La Foresta, F., Mammone, N., & Morabito, F. C. (2006). Automatic detection of critical epochs in coma-EEG using independent component analysis and higher order statistics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4234 LNCS - III, pp. 82-91). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4234 LNCS - III). Springer Verlag.