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 language||English (US)|
|Number of pages||6|
|Journal||IEEE Transactions on Neural Systems and Rehabilitation Engineering|
|State||Published - Jun 2005|
Bibliographical noteFunding 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.
- Brain-computer interface (BCI)
- Dipole source analysis
- Electroencephalography (EEG)
- Inverse problem
- Motor imagery