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• W2122832496 abstract "A new communication channel for severely handicapped people could be opened with a direct brain to computer interface (BCI). Such a system classifies electrical brain signals online. In a series of training sessions, where electroencephalograph (EEG) signals are recorded on the intact scalp, a classifier is trained to discriminate a limited number of different brain states. In a subsequent series of feedback sessions, where the subject is confronted with the classification results, the subject tries to reduce the number of misclassifications. In this study the relevance of different spectral components is analyzed: 1) on the training sessions to select optimal frequency bands for the feedback sessions and 2) on the feedback sessions to monitor changes." @default.
• W2122832496 created "2016-06-24" @default.
• W2122832496 creator A5005774851 @default.
• W2122832496 creator A5037161671 @default.
• W2122832496 date "1999-01-01" @default.
• W2122832496 modified "2023-10-12" @default.
• W2122832496 title "Frequency component selection for an EEG-based brain to computer interface" @default.
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• W2122832496 doi "https://doi.org/10.1109/86.808944" @default.
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