Motor imagery classification by means of source analysis methods

L. Qin, J. Deng, L. Ding, B. He

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

We report our investigation of classification of imagined left and right hand movements by applying source analysis methods. Independent component analysis (ICA) is used as a spatio-temporal filter, then equivalent dipole analysis and cortical current density imaging methods are applied to reconstruct equivalent sources, to aid classification of motor imagery tasks in a human subject. The classification was considered correct if the equivalent source was found over the motor cortex in the corresponding hemisphere. A classification rate of about 80% was achieved in the human subject studied using both the equivalent dipole analysis and the cortical, current density imaging analysis.

Original languageEnglish (US)
Pages (from-to)4356-4358
Number of pages3
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume26 VI
StatePublished - Dec 1 2004
EventConference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States
Duration: Sep 1 2004Sep 5 2004

Keywords

  • Brain Computer Interface
  • EEG
  • Independent component analysis
  • Inverse Solution
  • Source Analysis

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