The first Brain-Computer Interface utilizing a Turkish language model

One of the widely studied electroencephalography (EEG) based Brain-Computer Interface (BCI) set ups involves having subjects type letters based on so-called P300 signals generated by their brains in response to unpredictable stimuli. Due to the low signal-to-noise ratio (SNR) of EEG signals, current...

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Veröffentlicht in:	2013 21st Signal Processing and Communications Applications Conference (SIU) S. 1 - 4
Hauptverfasser:	Ulas, C., Cetin, M.
Format:	Tagungsbericht
Sprache:	Englisch Türkisch
Veröffentlicht:	IEEE 01.04.2013
Schlagworte:	Accuracy Brain modeling Brain-Computer Interface Brain-computer interfaces Electroencephalography Forward-Backward algorithm Hidden Markov Model Hidden Markov models language model Markov processes P300 speller Viterbi algorithm
ISBN:	9781467355629, 1467355623
Online-Zugang:	Volltext
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