L-SeqSleepNet: Whole-cycle long sequence modelling for automatic sleep staging
Human sleep is cyclical with a period of approximately 90 minutes, implying long temporal
dependency in the sleep data. Yet, exploring this long-term dependency when developing …
dependency in the sleep data. Yet, exploring this long-term dependency when developing …
Recsleepnet: An automatic sleep staging model based on feature reconstruction
H Nie, S Tu, L Xu - 2021 IEEE International Conference on …, 2021 - ieeexplore.ieee.org
S1eep staging via electroencephalogram (EEG) is the fundamental step to sleep quality
assessment and disease diagnose. Deep learning methods have been demonstrated to be …
assessment and disease diagnose. Deep learning methods have been demonstrated to be …
Brainsleepnet: Learning multivariate eeg representation for automatic sleep staging
Sleep is one of the most fundamental physiological activities of human beings. Automatic
sleep staging can efficiently assist human experts to diagnose the sleep health of people …
sleep staging can efficiently assist human experts to diagnose the sleep health of people …
A residual based attention model for EEG based sleep staging
Sleep staging is to score the sleep state of a subject into different sleep stages such as
Wake and Rapid Eye Movement (REM). It plays an indispensable role in the diagnosis and …
Wake and Rapid Eye Movement (REM). It plays an indispensable role in the diagnosis and …
SleepPrintNet: A multivariate multimodal neural network based on physiological time-series for automatic sleep staging
Sleep is one of the most fundamental physiological activities of human beings. Sleep
assessment based on physiological time-series can efficiently assist human experts to …
assessment based on physiological time-series can efficiently assist human experts to …
CAttSleepNet: automatic end-to-end sleep staging using attention-based deep neural networks on single-channel EEG
Accurate sleep staging results can be used to measure sleep quality, providing a reliable
basis for the prevention and diagnosis of sleep-related diseases. The key to sleep staging is …
basis for the prevention and diagnosis of sleep-related diseases. The key to sleep staging is …
SeqSleepNet: end-to-end hierarchical recurrent neural network for sequence-to-sequence automatic sleep staging
Automatic sleep staging has been often treated as a simple classification problem that aims
at determining the label of individual target polysomnography epochs one at a time. In this …
at determining the label of individual target polysomnography epochs one at a time. In this …
Real-time sleep staging using deep learning on a smartphone for a wearable EEG
We present the first real-time sleep staging system that uses deep learning without the need
for servers in a smartphone application for a wearable EEG. We employ real-time adaptation …
for servers in a smartphone application for a wearable EEG. We employ real-time adaptation …
LGSleepNet: an automatic sleep staging model based on local and global representation learning
Q Shen, J Xin, X Liu, Z Wang, C Li… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Sleep staging is an indispensable indicator for measuring sleep quality and evaluating
sleep disorders. Deep learning methods have been successfully applied to automatic sleep …
sleep disorders. Deep learning methods have been successfully applied to automatic sleep …
LWSleepNet: A lightweight attention-based deep learning model for sleep staging with singlechannel EEG
C Yang, B Li, Y Li, Y He, Y Zhang - Digital Health, 2023 - journals.sagepub.com
Introduction Sleep is vital to human health, and sleep staging is an essential process in
sleep assessment. However, manual classification is an inefficient task. Along with the …
sleep assessment. However, manual classification is an inefficient task. Along with the …