Brain activity investigation by EEG processing: Wavelet analysis, kurtosis and Renyi's entropy for artifact detection

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

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

Abstract

Electroencephalographic (EEG) recordings are employed in order to investigate the brain activity in neuropathological subjects. Unfortunately EEG 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. In this paper we propose a multiresolution analysis, based on EEG wavelet processing, to extract the cerebral EEG rhythms. We also present a method based on Renyi's entropy and kurtosis to automatically identify the Wavelet components affected by artifacts. Finally, we discuss as the joint use of wavelet analysis, kurtosis and Renyi's entropy allows for a deeper investigation of the brain activity and we discuss the capability of this technique to become an efficient preprocessing step to optimize artifact rejection from EEG. This is the first technique that exploits the peculiarities of EEG to Optimize EEG artifact detection.

Original languageEnglish
Title of host publicationProceedings of the 2007 International Conference on Information Acquisition, ICIA
Pages195-200
Number of pages6
DOIs
Publication statusPublished - 2007
EventInternational Conference on Information Acquisition, ICIA 2007 - Jeju City, Korea, Republic of
Duration: Jul 9 2007Jul 11 2007

Other

OtherInternational Conference on Information Acquisition, ICIA 2007
CountryKorea, Republic of
CityJeju City
Period7/9/077/11/07

Keywords

  • Artifact removal
  • EEG
  • Reniy's entropy
  • Wavelet analysis

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management

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