Automatic diagnosis of sleep apnea from biomedical signals using artificial intelligence techniques: Methods, challenges, and future works
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 slee**. This reduction in …
apnea may last for a few seconds and happen for many while slee**. This reduction in …
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 …
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 …
Phase Space Graph Convolutional Network for Chaotic Time Series Learning
W Ren, N **, L OuYang - IEEE Transactions on Industrial …, 2024 - ieeexplore.ieee.org
Complex network has been a powerful tool for time series analysis by encoding dynamical
temporal information in network topology. In this article, we introduce a framework to build a …
temporal information in network topology. In this article, we introduce a framework to build a …
Classification of normal and depressed EEG signals based on centered correntropy of rhythms in empirical wavelet transform domain
A widespread brain disorder of present days is depression which influences 264 million of
the world's population. Depression may cause diverse undesirable consequences, including …
the world's population. Depression may cause diverse undesirable consequences, including …
End-to-end fatigue driving EEG signal detection model based on improved temporal-graph convolution network
H Jia, Z **ao, P Ji - Computers in Biology and Medicine, 2023 - Elsevier
Fatigue driving is one of the leading causes of traffic accidents, so fatigue driving detection
technology plays a crucial role in road safety. The physiological information-based fatigue …
technology plays a crucial role in road safety. The physiological information-based fatigue …
Automatic sleep stage classification: A light and efficient deep neural network model based on time, frequency and fractional Fourier transform domain features
Y You, X Zhong, G Liu, Z Yang - Artificial Intelligence in Medicine, 2022 - Elsevier
This work proposed a novel method for automatic sleep stage classification based on the
time, frequency, and fractional Fourier transform (FRFT) domain features extracted from a …
time, frequency, and fractional Fourier transform (FRFT) domain features extracted from a …
SHNN: A single-channel EEG sleep staging model based on semi-supervised learning
Sleep staging is an essential step in the diagnosis and treatment of sleep-related diseases.
Currently, most supervised learning models face the problem of insufficient labeled data. In …
Currently, most supervised learning models face the problem of insufficient labeled data. In …
EEG sub-bands based sleep stages classification using Fourier Synchrosqueezed transform features
Sleep is a state that coordinates all the human body's major functions. Irregularity of sleep or
its deprivation disrupts the physical and mental state of a person. An automated method that …
its deprivation disrupts the physical and mental state of a person. An automated method that …
Self-supervised learning for label-efficient sleep stage classification: A comprehensive evaluation
The past few years have witnessed a remarkable advance in deep learning for EEG-based
sleep stage classification (SSC). However, the success of these models is attributed to …
sleep stage classification (SSC). However, the success of these models is attributed to …