A comparative review on sleep stage classification methods in patients and healthy individuals

R Boostani, F Karimzadeh, M Nami - Computer methods and programs in …, 2017 - Elsevier
Background and objective: Proper scoring of sleep stages can give clinical information on
diagnosing patients with sleep disorders. Since traditional visual scoring of the entire sleep …

A review of automated sleep stage scoring based on physiological signals for the new millennia

O Faust, H Razaghi, R Barika, EJ Ciaccio… - Computer methods and …, 2019 - Elsevier
Abstract Background and Objective Sleep is an important part of our life. That importance is
highlighted by the multitude of health problems which result from sleep disorders. Detecting …

A driving fatigue feature detection method based on multifractal theory

F Wang, H Wang, X Zhou, R Fu - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Driving fatigue seriously threatens traffic safety. In our work, the multifractal detrended
fluctuation analysis (MF-DFA) method is proposed to detect driver fatigue caused by driving …

Ensemble SVM method for automatic sleep stage classification

E Alickovic, A Subasi - IEEE Transactions on Instrumentation …, 2018 - ieeexplore.ieee.org
Sleep scoring is used as a diagnostic technique in the diagnosis and treatment of sleep
disorders. Automated sleep scoring is crucial, since the large volume of data should be …

Learning machines and slee** brains: automatic sleep stage classification using decision-tree multi-class support vector machines

T Lajnef, S Chaibi, P Ruby, PE Aguera… - Journal of neuroscience …, 2015 - Elsevier
Background Sleep staging is a critical step in a range of electrophysiological signal
processing pipelines used in clinical routine as well as in sleep research. Although the …

Analysis and classification of sleep stages based on difference visibility graphs from a single-channel EEG signal

G Zhu, Y Li, P Wen - IEEE journal of biomedical and health …, 2014 - ieeexplore.ieee.org
The existing sleep stages classification methods are mainly based on time or frequency
features. This paper classifies the sleep stages based on graph domain features from a …

A decision support system for automatic sleep staging from EEG signals using tunable Q-factor wavelet transform and spectral features

AR Hassan, MIH Bhuiyan - Journal of neuroscience methods, 2016 - Elsevier
Background Automatic sleep scoring is essential owing to the fact that conventionally a large
volume of data have to be analyzed visually by the physicians which is onerous, time …

Automatic sleep stage recurrent neural classifier using energy features of EEG signals

YL Hsu, YT Yang, JS Wang, CY Hsu - Neurocomputing, 2013 - Elsevier
This paper presents a recurrent neural classifier for automatically classifying sleep stages
based on energy features from the EEG signal of the Fpz− Cz channel. The energy features …

An ensemble system for automatic sleep stage classification using single channel EEG signal

B Koley, D Dey - Computers in biology and medicine, 2012 - Elsevier
The present work aims at automatic identification of various sleep stages like, sleep stages
1, 2, slow wave sleep (sleep stages 3 and 4), REM sleep and wakefulness from single …

Automatic stage scoring of single-channel sleep EEG by using multiscale entropy and autoregressive models

SF Liang, CE Kuo, YH Hu, YH Pan… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
In this paper, we propose an automatic sleep-scoring method combining multiscale entropy
(MSE) and autoregressive (AR) models for single-channel EEG and to assess the …