Activity Prediction for Localizing the Events in Imagined Speech EEG Signals

Imagined speech electroencephalogram (EEG) signals are often collected for longer durations than necessary, leading to a difficulty in understanding the generation of EEG during the task as it is likely that most of the data collected is that of resting state. Developing a filter to identify the seg...

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Vydané v:	The ... International Winter Conference on Brain-Computer Interface s. 1 - 5
Hlavní autori:	Balasubramanian, Arun, Pandey, Kartik, Veer, Gautam, Samanta, Debasis
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 24.02.2025
Predmet:	Accuracy EEG Electroencephalography Feature extraction feature importance frequency analysis Image segmentation Imagined speech Information filters Location awareness neural decoding Neuroscience resting state Signal processing Speech processing Vectors
ISSN:	2572-7672
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