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

IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
Baharan KamousiBin He

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.

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Related Concepts

In Silico
Electroencephalography
Imagination
Critical Incident Technique
Potentials, Event-Related
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