A novel deep-learning model based on τ-shaped convolutional network (τNet) with long short-term memory (LSTM) for physiological fatigue detection from EEG and EOG signals.
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%0 Journal Article
%1 journals/mbec/HeZLQ24
%A He, Le
%A Zhang, Li
%A Lin, Xiangtian
%A Qin, Yunfeng
%D 2024
%J Medical Biol. Eng. Comput.
%K dblp
%N 6
%P 1781-1793
%T A novel deep-learning model based on τ-shaped convolutional network (τNet) with long short-term memory (LSTM) for physiological fatigue detection from EEG and EOG signals.
%U http://dblp.uni-trier.de/db/journals/mbec/mbec62.html#HeZLQ24
%V 62
@article{journals/mbec/HeZLQ24,
added-at = {2024-05-17T00:00:00.000+0200},
author = {He, Le and Zhang, Li and Lin, Xiangtian and Qin, Yunfeng},
biburl = {https://www.bibsonomy.org/bibtex/2a3a6ce2b1d28ea827cc8b520c83257df/dblp},
ee = {https://doi.org/10.1007/s11517-024-03033-y},
interhash = {7da8ad6e7f34608857d1fe29b32818e2},
intrahash = {a3a6ce2b1d28ea827cc8b520c83257df},
journal = {Medical Biol. Eng. Comput.},
keywords = {dblp},
month = {June},
number = 6,
pages = {1781-1793},
timestamp = {2024-05-20T07:11:32.000+0200},
title = {A novel deep-learning model based on τ-shaped convolutional network (τNet) with long short-term memory (LSTM) for physiological fatigue detection from EEG and EOG signals.},
url = {http://dblp.uni-trier.de/db/journals/mbec/mbec62.html#HeZLQ24},
volume = 62,
year = 2024
}
