Cascaded LSTM recurrent neural network for automated sleep stage classification using single-channel EEG signals

Automated evaluation of a subject's neurocognitive performance (NCP) is a relevant topic in neurological and clinical studies. NCP represents the mental/cognitive human capacity in performing a specific task. It is difficult to develop the study protocols as the subject's NCP changes in a...

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Vydáno v:	Computers in biology and medicine Ročník 106; s. 71 - 81
Hlavní autoři:	Michielli, Nicola, Acharya, U. Rajendra, Molinari, Filippo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Elsevier Ltd 01.03.2019 Elsevier Limited
Témata:	Adult Algorithms Classification Cognition Cognitive ability Drowsiness EEG EEG signals Electroencephalography Event-related potentials Eye movements Feature extraction Female Human performance Humans Internal Medicine Long short-term memory Male Neural networks Neural Networks, Computer Neurocognitive performance NREM sleep Other Principal components analysis Protocol (computers) Recurrent neural networks REM sleep Signal Processing, Computer-Assisted Sleep Sleep analysis Sleep and wakefulness Sleep deprivation Sleep Stages - physiology Wakefulness Long short-term memory Recurrent neural networks Sleep analysis EEG signals Neurocognitive performance
ISSN:	0010-4825, 1879-0534, 1879-0534
On-line přístup:	Získat plný text
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