Deep learning in physiological signal data: A survey
Deep Learning (DL), a successful promising approach for discriminative and generative
tasks, has recently proved its high potential in 2D medical imaging analysis; however …
tasks, has recently proved its high potential in 2D medical imaging analysis; however …
Automatic diagnosis of sleep apnea from biomedical signals using artificial intelligence techniques: Methods, challenges, and future works
P Moridian, A Shoeibi, M Khodatars… - … : Data Mining and …, 2022 - Wiley Online Library
Apnea is a sleep disorder that stops or reduces airflow for a short time during sleep. Sleep
apnea may last for a few seconds and happen for many while sleeping. This reduction in …
apnea may last for a few seconds and happen for many while sleeping. This reduction in …
An attention-based deep learning approach for sleep stage classification with single-channel EEG
Automatic sleep stage mymargin classification is of great importance to measure sleep
quality. In this paper, we propose a novel attention-based deep learning architecture called …
quality. In this paper, we propose a novel attention-based deep learning architecture called …
Multi-view spatial-temporal graph convolutional networks with domain generalization for sleep stage classification
Sleep stage classification is essential for sleep assessment and disease diagnosis.
Although previous attempts to classify sleep stages have achieved high classification …
Although previous attempts to classify sleep stages have achieved high classification …
Automatic sleep stage classification using temporal convolutional neural network and new data augmentation technique from raw single-channel EEG
Background and objective: This paper presents a new framework for automatic classification
of sleep stages using a deep learning algorithm from single-channel EEG signals. Each …
of sleep stages using a deep learning algorithm from single-channel EEG signals. Each …
Automatic sleep stage classification: From classical machine learning methods to deep learning
RN Sekkal, F Bereksi-Reguig… - … Signal Processing and …, 2022 - Elsevier
Background and objectives The classification of sleep stages is a preliminary exam that
contributes to the diagnosis of possible sleep disorders. However, it is a tedious and time …
contributes to the diagnosis of possible sleep disorders. However, it is a tedious and time …
SalientSleepNet: Multimodal salient wave detection network for sleep staging
Sleep staging is fundamental for sleep assessment and disease diagnosis. Although
previous attempts to classify sleep stages have achieved high classification performance …
previous attempts to classify sleep stages have achieved high classification performance …
A single-channel EEG based automatic sleep stage classification method leveraging deep one-dimensional convolutional neural network and hidden Markov model
B Yang, X Zhu, Y Liu, H Liu - Biomedical Signal Processing and Control, 2021 - Elsevier
Sleep stage classification is an essential process for analyzing sleep and diagnosing sleep
related disorders. Sleep staging by visual inspection of expert is a labor-intensive task and …
related disorders. Sleep staging by visual inspection of expert is a labor-intensive task and …
Automated detection of sleep stages using deep learning techniques: A systematic review of the last decade (2010–2020)
Sleep is vital for one's general well-being, but it is often neglected, which has led to an
increase in sleep disorders worldwide. Indicators of sleep disorders, such as sleep …
increase in sleep disorders worldwide. Indicators of sleep disorders, such as sleep …
SleepContextNet: A temporal context network for automatic sleep staging based single-channel EEG
C Zhao, J Li, Y Guo - Computer Methods and Programs in Biomedicine, 2022 - Elsevier
Background and objective: Single-channel EEG is the most popular choice of sensing
modality in sleep staging studies, because it widely conforms to the sleep staging …
modality in sleep staging studies, because it widely conforms to the sleep staging …