Classification of motor imagery tasks for brain-computer interface applications by means of two equivalent dipoles analysis

Baharan Kamousi, Zhongming Liu, Bin He

Research output: Contribution to journalArticlepeer-review

98 Scopus citations

Abstract

We have developed a novel approach using source analysis for classifying motor imagery tasks. Two-equivalent-dipoles analysis was proposed to aid classification of motor imagery tasks for brain-computer interface (BCI) applications. By solving the electroencephalography (EEG) inverse problem of single trial data, it is found that the source analysis approach can aid classification of motor imagination of left- or right-hand movement without training. In four human subjects, an averaged accuracy of classification of 80% was achieved. The present study suggests the merits and feasibility of applying EEG inverse solutions to BCI applications from noninvasive EEG recordings.

Original languageEnglish (US)
Pages (from-to)166-171
Number of pages6
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume13
Issue number2
DOIs
StatePublished - Jun 2005

Bibliographical note

Funding Information:
Manuscript received January 6, 2005; revised January 29, 2005; accepted February 1, 2005. This work was supported in part by the National Science Foundation (NSF) under Grant BES-0411898, in part by NSF CAREER Award BES-9875344, and in part by the National Institutes of Health under Grant R01EB00178.

Keywords

  • Brain-computer interface (BCI)
  • Dipole source analysis
  • Electroencephalography (EEG)
  • Inverse problem
  • Motor imagery

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