A review of automated sleep stage based on EEG signals
X Zhang, X Zhang, Q Huang, Y Lv, F Chen - Biocybernetics and Biomedical …, 2024 - Elsevier
Sleep disorders have increasingly impacted healthy lifestyles. Accurate scoring of sleep
stages is crucial for diagnosing patients with sleep disorders. The precision of sleep staging …
stages is crucial for diagnosing patients with sleep disorders. The precision of sleep staging …
Current status and prospects of automatic sleep stages scoring
The scoring of sleep stages is one of the essential tasks in sleep analysis. Since a manual
procedure requires considerable human and financial resources, and incorporates some …
procedure requires considerable human and financial resources, and incorporates some …
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 …
Global adaptive transformer for cross-subject enhanced EEG classification
Due to the individual difference, EEG signals from other subjects (source) can hardly be
used to decode the mental intentions of the target subject. Although transfer learning …
used to decode the mental intentions of the target subject. Although transfer learning …
An ensemble voting approach with innovative multi-domain feature fusion for neonatal sleep stratification
A limited number of electroencephalography (EEG) channels are useful for neonatal sleep
classification, particularly in the Internet of Medical Things (IoMT) field, where compact and …
classification, particularly in the Internet of Medical Things (IoMT) field, where compact and …
Multimodal Polysomnography Based Automatic Sleep Stage Classification via Multiview Fusion Network
Sleep staging is a standard diagnostic method for evaluating sleep quality, which would
enable early diagnosis of sleep disorders as well as mental diseases. Polysomnography …
enable early diagnosis of sleep disorders as well as mental diseases. Polysomnography …
FlexSleepTransformer: a transformer-based sleep staging model with flexible input channel configurations
Y Guo, M Nowakowski, W Dai - Scientific Reports, 2024 - nature.com
Clinical sleep diagnosis traditionally relies on polysomnography (PSG) and expert manual
classification of sleep stages. Recent advancements in deep learning have shown promise …
classification of sleep stages. Recent advancements in deep learning have shown promise …
Reliable automatic sleep stage classification based on hybrid intelligence
Sleep staging is a vital aspect of sleep assessment, serving as a critical tool for evaluating
the quality of sleep and identifying sleep disorders. Manual sleep staging is a laborious …
the quality of sleep and identifying sleep disorders. Manual sleep staging is a laborious …
SQI-DOANet: electroencephalogram-based deep neural network for estimating signal quality index and depth of anaesthesia
Objective. Monitoring the depth of anaesthesia (DOA) during surgery is of critical
importance. However, during surgery electroencephalography (EEG) is usually subject to …
importance. However, during surgery electroencephalography (EEG) is usually subject to …
BiTS-SleepNet: An Attention-Based Two Stage Temporal-Spectral Fusion Model for Sleep Staging With Single-Channel EEG
Automated sleep staging is crucial for assessing sleep quality and diagnosing sleep-related
diseases. Single-channel EEG has attracted significant attention due to its portability and …
diseases. Single-channel EEG has attracted significant attention due to its portability and …