Determining a continuous marker for sleep depth
Detection and quantification of sleep arousals is an important issue, as the frequent arousals
are known to reduce the quality of sleep and cause daytime sleepiness. In typical sleep …
are known to reduce the quality of sleep and cause daytime sleepiness. In typical sleep …
A comparative review on sleep stage classification methods in patients and healthy individuals
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 …
diagnosing patients with sleep disorders. Since traditional visual scoring of the entire sleep …
A novel method for sleep-stage classification based on sonification of sleep electroencephalogram signals using wavelet transform and recurrent neural network
Introduction: Visual sleep-stage scoring is a time-consuming technique that cannot extract
the nonlinear characteristics of electroencephalogram (EEG). This article presents a novel …
the nonlinear characteristics of electroencephalogram (EEG). This article presents a novel …
Examining the relevance with sleep stages of time domain features of EEG, EOG, and chin EMG signals
Sleep staging has an important role in determining sleep disorders such as sleepiness,
human fatigue etc. Sleep staging is generally done according to Rechtschaffen and Kales …
human fatigue etc. Sleep staging is generally done according to Rechtschaffen and Kales …
A decision support system for automated identification of sleep stages from single-channel EEG signals
A decision support system for automated detection of sleep stages can alleviate the burden
of medical professionals of manually annotating a large bulk of data, expedite sleep disorder …
of medical professionals of manually annotating a large bulk of data, expedite sleep disorder …
Combination of expert knowledge and a genetic fuzzy inference system for automatic sleep staging
Objective: In this paper, the genetic fuzzy inference system based on expert knowledge for
automatic sleep staging was developed. Methods: Eight features, including temporal and …
automatic sleep staging was developed. Methods: Eight features, including temporal and …
Artificial neural network and wavelet based automated detection of sleep spindles, REM sleep and wake states
RK Sinha - Journal of medical systems, 2008 - Springer
Backpropagation artificial neural network (ANN) has been designed to classify sleep–wake
stages. Four hours continuous three channel polygraphic signals such as EEG …
stages. Four hours continuous three channel polygraphic signals such as EEG …
A comparative study on classification of sleep stage based on EEG signals using feature selection and classification algorithms
Sleep scoring is one of the most important diagnostic methods in psychiatry and neurology.
Sleep staging is a time consuming and difficult task undertaken by sleep experts. This study …
Sleep staging is a time consuming and difficult task undertaken by sleep experts. This study …
An intelligent system for diagnosing sleep stages using wavelet coefficients
M Vatankhah, MR Akbarzadeh-T… - The 2010 international …, 2010 - ieeexplore.ieee.org
Human sleep is divided into two segments, Rapid Eye Movement (REM) sleep and Non-
REM (NREM) sleep. NREM sleep is further divided into 4 stages. Sleep staging attempts to …
REM (NREM) sleep. NREM sleep is further divided into 4 stages. Sleep staging attempts to …
Sleep quality detection based on EEG signals using transfer support vector machine algorithm
W Wen - Frontiers in Neuroscience, 2021 - frontiersin.org
Background In recent years, with the acceleration of life rhythm and increased pressure, the
problem of sleep disorders has become more and more serious. It affects people's quality of …
problem of sleep disorders has become more and more serious. It affects people's quality of …