A comparative study on classification of sleep stage based on EEG signals using feature selection and classification algorithms

B Şen, M Peker, A Çavuşoğlu, FV Çelebi - Journal of medical systems, 2014 - Springer
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 …

Complex networks approach for EEG signal sleep stages classification

M Diykh, Y Li - Expert Systems with Applications, 2016 - Elsevier
Sleep stage scoring is a challenging task. Most of existing sleep stage classification
approaches rely on analysing electroencephalography (EEG) signals in time or frequency …

Automatic sleep stages classification using optimize flexible analytic wavelet transform

S Taran, PC Sharma, V Bajaj - Knowledge-Based Systems, 2020 - Elsevier
Sleep stages classification avails the diagnosis and treatment of sleep-related disorders.
The traditional visual inspection methods used by sleep-experts are time-consuming and …

An efficient sleep scoring system based on EEG signal using complex-valued machine learning algorithms

M Peker - Neurocomputing, 2016 - Elsevier
Sleep staging is a significant step in the diagnosis and treatment of sleep disorders. Sleep
scoring is a time-consuming and difficult process. Given that sleep scoring requires expert …

A new approach for automatic sleep scoring: Combining Taguchi based complex-valued neural network and complex wavelet transform

M Peker - Computer methods and programs in biomedicine, 2016 - Elsevier
Automatic classification of sleep stages is one of the most important methods used for
diagnostic procedures in psychiatry and neurology. This method, which has been developed …

Multiclass sleep stage classification using artificial intelligence based time-frequency distribution and CNN

SK Khare, V Bajaj, S Taran, GR Sinha - Artificial intelligence-based brain …, 2022 - Elsevier
Background: The conventional sleep stage scoring uses interview, questionnaire, and visual
inspection by trained neurologists. These methodologies are time taking, inefficient, and …

Effect of feature extraction on automatic sleep stage classification by artificial neural network

M Prucnal, AG Polak - Metrology and Measurement Systems, 2017 - yadda.icm.edu.pl
EEG signal-based sleep stage classification facilitates an initial diagnosis of sleep disorders.
The aim of this study was to compare the efficiency of three methods for feature extraction …

Human sleep scoring based on K-nearest neighbors

S Qureshi, S Karrila… - Turkish Journal of …, 2018 - journals.tubitak.gov.tr
Human sleep is one of the essential indicators that gauge the overall health and well-being.
Presently, it is common for people to face issues related to sleep. Various biomedical signals …

[HTML][HTML] Unsupervised Multitaper Spectral Method for Identifying REM Sleep in Intracranial EEG Recordings Lacking EOG/EMG Data

KQ Lepage, S Jain, A Kvavilashvili, M Witcher… - Bioengineering, 2023 - mdpi.com
A large number of human intracranial EEG (iEEG) recordings have been collected for
clinical purposes, in institutions all over the world, but the vast majority of these are …

Collaborative sleep electroencephalogram data analysis based on improved empirical mode decomposition and clustering algorithm

X Zheng, X Yin, X Shao, Y Li, X Yu - Complexity, 2020 - Wiley Online Library
Sleep‐related diseases seriously affect the life quality of patients. Sleep stage classification
(or sleep staging), which studies the human sleep process and classifies the sleep stages, is …