title: [Classification of EEG Patterns of Imagined Rhythmic Movements of the Fingers of One Hand].
abstract: The article presents the results of classification of EEG patterns registered during imagined rhytmic movements of the fingers of the right hand (little, thumb, index, middle fingers) in 8 healthy subjects. The subjects imagined finger movements in a given rhythm; no external stimuli were used. A two-level committee of classifiers was developed for decoding: the first level included support vector machines and artificial neural networks; the second level included artificial neural network used for generalizing. As the key parameters for classification, we used the area of zone under the envelope of EEG signal and the length of the envelope calculated in sliding time window for leads F3, C3 and Cz in system 10-20 were chosen as the key features for signals of sensorimotor and adjoining frontal area cortex contralateral to movements. The accuracy of classification of single trials for 4 movements averaged for all subjects for the pair of leads F3-C3 was 50 ± 7% [SD] (maximal - 58%); for the pair of leads C3-Cz, 46 ± 11% [SD] (maximal - 62%); theoretical guessing level is 25%.
authors.forename: L A
authors.initials: LA
authors.lastname: Stankevich
authors.forename: K M
authors.initials: KM
authors.lastname: Sonkin
authors.forename: N V
authors.initials: NV
authors.lastname: Shemyakina
authors.forename: Zh V
authors.initials: ZhV
authors.lastname: Nagornova
authors.forename: J G
authors.initials: JG
authors.lastname: Khomenko
authors.forename: D S
authors.initials: DS
authors.lastname: Perets
authors.forename: A V
authors.initials: AV
authors.lastname: Koval
mesh_terms: D004569:Electroencephalography; D005385:Fingers / Q000502:physiology*; D006225:Hand; D006801:Humans; D009068:Movement; D016571:Neural Networks, Computer; D060388:Support Vector Machine