Classification of Drowsiness Levels Based on a Deep Spatio-Temporal Convolutional Bidirectional LSTM Network Using Electroencephalography Signals

Non-invasive brain-computer interfaces (BCI) have been developed for recognizing human mental states with high accuracy and for decoding various types of mental conditions. In particular, accurately decoding a pilot’s mental state is a critical issue as more than 70% of aviation accidents are caused...

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Detalles Bibliográficos
Autores principales: Jeong, Ji-Hoon, Yu, Baek-Woon, Lee, Dae-Hyeok, Lee, Seong-Whan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6956039/
https://www.ncbi.nlm.nih.gov/pubmed/31795445
http://dx.doi.org/10.3390/brainsci9120348

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6956039/
https://www.ncbi.nlm.nih.gov/pubmed/31795445
http://dx.doi.org/10.3390/brainsci9120348

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