Focal artifact removal from ongoing EEG - A hybrid approach based on spatially-constrained ICA and wavelet de-noising

Muhammad Tahir Akhtar, Christopher J. James

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

12 Citations (Scopus)

Abstract

Detecting artifacts produced in electroencephalographic (EEG) data by muscle activity, eye blinks and electrical noise, etc., is an important problem in EEG signal processing research. These artifacts must be corrected before further analysis because it renders subsequent analysis very error-prone. One solution is to reject the data segment if artifact is present during the observation interval, however, the rejected data segment could contain important information masked by the artifact. It has already been demonstrated that independent component analysis (ICA) can be an effective and applicable method for EEG de-noising. The goal of this paper is to propose a framework, based on ICA and wavelet denoising (WD), to improve the pre-processing of EEG signals. In particular we employ the concept of spatially-constrained ICA (SCICA) to extract artifact-only independent components (ICs) from the given EEG data, use WD to remove any brain activity from extracted artifacts, and finally project back the artifacts to be subtracted from EEG signals to get clean EEG data. The main advantage of the proposed approach is faster computation, as all ICs are not identified in the usual manner due to the square mixing assumption. Simulation results demonstrate the effectiveness of the proposed approach in removing focal artifacts that can be well separated by SCICA.

Original languageEnglish
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEngineering the Future of Biomedicine, EMBC 2009
PublisherIEEE Computer Society
Pages4027-4030
Number of pages4
ISBN (Print)9781424432967
DOIs
Publication statusPublished - Dec 1 2009
Event31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States
Duration: Sep 2 2009Sep 6 2009

Publication series

NameProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

Conference

Conference31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
CountryUnited States
CityMinneapolis, MN
Period9/2/099/6/09

Keywords

  • Algorithms
  • Artifacts
  • Artificial Intelligence
  • Brain
  • Brain Mapping
  • Brain Mapping: methods
  • Brain: pathology
  • Computer Simulation
  • Data Interpretation, Statistical
  • Electroencephalography
  • Electroencephalography: instrumentation
  • Electroencephalography: methods
  • Humans
  • Pattern Recognition, Automated
  • Pattern Recognition, Automated: methods
  • Signal Processing, Computer-Assisted
  • Software
  • Time Factors

ASJC Scopus subject areas

  • Cell Biology
  • Developmental Biology
  • Biomedical Engineering
  • Medicine(all)

Fingerprint Dive into the research topics of 'Focal artifact removal from ongoing EEG - A hybrid approach based on spatially-constrained ICA and wavelet de-noising'. Together they form a unique fingerprint.

  • Cite this

    Akhtar, M. T., & James, C. J. (2009). Focal artifact removal from ongoing EEG - A hybrid approach based on spatially-constrained ICA and wavelet de-noising. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 (pp. 4027-4030). [5333725] (Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009). IEEE Computer Society. https://doi.org/10.1109/IEMBS.2009.5333725