Sleep scoring using artificial neural networks

M Ronzhina, O Janoušek, J Kolářová, M Nováková… - Sleep medicine …, 2012 - Elsevier
Rapid development of computer technologies leads to the intensive automation of many
different processes traditionally performed by human experts. One of the spheres …

Computer based sleep staging: challenges for the future

STB Hamida, B Ahmed - 2013 7th IEEE GCC Conference and …, 2013 - ieeexplore.ieee.org
Studies have shown that patients suffering from sleep deprivation have a risk for
hypertension, diabetes and depression that is higher than normal sleepers. Treatment for all …

Combining machine learning models for the automatic detection of EEG arousals

I Fernández-Varela, E Hernández-Pereira… - Neurocomputing, 2017 - Elsevier
Electroencephalographic (EEG) arousals are related to sleep fragmentation and the
consequent daytime sleepiness, and are usually detected by visual inspection of sleep …

State-of-the-art sleep arousal detection evaluated on a comprehensive clinical dataset

F Ehrlich, T Sehr, M Brandt, M Schmidt, H Malberg… - Scientific Reports, 2024 - nature.com
Aiming to apply automatic arousal detection to support sleep laboratories, we evaluated an
optimized, state-of-the-art approach using data from daily work in our university hospital …

Large-scale validation of an automatic EEG arousal detection algorithm using different heterogeneous databases

D Alvarez-Estevez, I Fernández-Varela - Sleep Medicine, 2019 - Elsevier
Objective To assess the validity of an automatic EEG arousal detection algorithm using large
patient samples and different heterogeneous databases. Methods Automatic scorings were …

A simple and robust method for the automatic scoring of EEG arousals in polysomnographic recordings

I Fernández-Varela, D Alvarez-Estevez… - Computers in Biology …, 2017 - Elsevier
Background Clinical diagnosis of sleep disorders relies on the polysomnographic test to
examine the neurophysiological markers of the sleep process. In this test, the recording of …

Method and apparatus for determining sleep states

U Abeyratne, V Swarnkar - US Patent 10,575,751, 2020 - Google Patents
An apparatus is provided for detecting Macro Sleep Architecture states of a subject such as
WAKE, NREM and REM sleep from a subject's EEG. The apparatus includes an EEG digital …

A hybrid machine learning model for classifying time series

A Elen, E Avuçlu - Neural Computing and Applications, 2022 - Springer
A time series is a sequence of numerical data points in equal time intervals and/or
successive order. Time series are used in many fields to understand the behavior of …

Sleep Stage Classification: A Deep Learning Approach

AA Gharbali - 2018 - search.proquest.com
Sleep occupies significant part of human life. The diagnoses of sleep related disorders are
of great importance. To record specific physical and electrical activities of the brain and …

Uyku evrelerinin EEG işaretleri kullanılarak sınıflandırılmasında yeni bir yaklaşım

M Yıldız - 2009 - search.proquest.com
Bu çalışmada uyku evrelerini sınıflandırma amacıyla EEG işaretlerinden çıkartılan
özelliklerin uyku evrelerini ne ölçüde ayrıştırdığını belirlemek amacıyla yöntemler sunulmuş …