A self-paced brain interface system that uses movement related potentials and changes in the power of brain rhythms

TitleA self-paced brain interface system that uses movement related potentials and changes in the power of brain rhythms
Publication TypeJournal Article
Year of Publication2007
AuthorsFatourechi, M., G. E. Birch, and R. K. Ward
JournalJ Comput Neurosci
Volume23
Pagination21-37
Date PublishedAug
Abstract

Movement execution results in the simultaneous generation of movement-related potentials (MRP) as well as changes in the power of Mu and Beta rhythms. This paper proposes a new self-paced multi-channel BI that combines features extracted from MRPs and from changes in the power of Mu and Beta rhythms. We developed a new algorithm to classify the high-dimensional feature space. It uses a two-stage multiple-classifier system (MCS). First, an MCS classifies each neurological phenomenon separately using the information extracted from specific EEG channels (EEG channels are selected by a genetic algorithm). In the second stage, another MCS combines the outputs of MCSs developed in the first stage. Analysis of the data of four able-bodied subjects shows the superior performance of the proposed algorithm compared with a scheme where the features were all combined in a single feature vector and then classified.

URLhttp://dx.doi.org/10.1007/s10827-006-0017-3
DOI10.1007/s10827-006-0017-3

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