EEG classification by learning vector quantization.

D Flotzinger; J Kalcher; G Pfurtscheller

doi:10.1515/bmte.1992.37.12.303

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EEG classification by learning vector quantization.

D Flotzinger·J Kalcher·G Pfurtscheller

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Abstract

EEG classification using Learning Vector Quantization (LVQ) is introduced on the basis of a Brain-Computer Interface (BCI) built in Graz, where a subject controlled a cursor in one dimension on a monitor using potentials recorded from the intact scalp. The method of classification with LVQ is described in detail along with first results on a subject who participated in four on-line cursor control sessions. Using this data, extensive off-line experiments were performed to show the influence of the various parameters of the classifier and the extracted features of the EEG on the classification results.

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Algorithms Dominance, Cerebral Electroencephalography Humans Motor Cortex Neural Networks, Computer Signal Processing, Computer-Assisted Somatosensory Cortex User-Computer Interface Journal Article Research Support, Non-U.S. Gov't

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D Flotzinger, J Kalcher, G Pfurtscheller. 1992. EEG classification by learning vector quantization.. https://doi.org/10.1515/bmte.1992.37.12.303

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