Multiresolution ICA for artifact identification from electroencephalographic recordings

Nadia Mammone, Giuseppina Inuso, Fabio La Foresta, Francesco Carlo Morabito

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

Abstract

This paper addresses the issue of artifact extraction from Electroencephalographic (EEG) signals and introduces a new technique for EEG artifact removal, based on the joint use of Wavelet transform and Independent Component Analysis (WICA). In fact, EEG recordings are often contaminated by the artifacts, signals that have non-cerebral origin and that might mimic cognitive or pathologic activity and therefore distort the analysis of EEG. The proposed technique extracts the artifacts taking into account the frequencies of the four major EEG rhythms. An artificial artifact-laden EEG dataset was created mixing a real EEG with a set of synthesized artifacts and the performance of WICA was measured. WICA had the best artifact separation performance for every kind of artifact with respect to other techniques and allowed for minimum information loss.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages680-687
Number of pages8
Volume4692 LNAI
EditionPART 1
Publication statusPublished - 2007
Event11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007 - Vietri sul Mare, Italy
Duration: Sep 12 2007Sep 14 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4692 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007
CountryItaly
CityVietri sul Mare
Period9/12/079/14/07

Keywords

  • Artifacts
  • EEG
  • Independent component analysis
  • Wavelet transform

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Fingerprint Dive into the research topics of 'Multiresolution ICA for artifact identification from electroencephalographic recordings'. Together they form a unique fingerprint.

  • Cite this

    Mammone, N., Inuso, G., La Foresta, F., & Morabito, F. C. (2007). Multiresolution ICA for artifact identification from electroencephalographic recordings. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 4692 LNAI, pp. 680-687). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4692 LNAI, No. PART 1).