Hidden Markov Models Used for the Offline Classification of EEG Data - Hidden Markov-Modelle, verwendet zur Offline-Klassifikation von EEG-Daten
- 1 January 1999
- journal article
- Published by Walter de Gruyter GmbH in Biomedizinische Technik/Biomedical Engineering
- Vol. 44 (6), 158-162
- https://doi.org/10.1515/bmte.1999.44.6.158
Abstract
Hidden Markov models (HMM) are introduced for the offline classification of single-trail EEG data in a brain-computer-interface (BCI). The HMMs are used to classify Hjorth parameters calculated from bipolar EEG data, recorded during the imagination of a left or right hand movement. The effects of different types of HMMs on the recognition rate are discussed. Furthermore a comparison of the results achieved with the linear discriminant (LD) and the HMM, is presented.Keywords
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