Results 21 to 30 of about 148,378 (289)

Evaluation of sleep stage classification using feature importance of EEG signal for big data healthcare

IJAIN (International Journal of Advances in Intelligent Informatics), 2023
Sleep analysis is widely and experimentally considered due to its importance to body health care. Since its sufficiency is essential for a healthy life, people often spend almost a third of their lives sleeping.
Mera Kartika Delimayanti, Mauldy Laya, Anggi Mardiyono, Bambang Warsuta, Reisa Siva Nandika, Mohammad Reza Faisal   +5 more
doaj   +1 more source

Pitfalls of AHI system of severity grading in obstructive sleep apnoea [PDF]

Sleep Science
Obstructive sleep apnoea (OSA) is the major underlying co-morbidity in many of the non-communicable diseases (NCD) due to obesity as a common risk factor.
Rashmi Soori, Nandakishore Baikunje, Ivor D’sa, Navneet Bhushan, Belur Nagabhushana, Giridhar Belur Hosmane   +5 more
doaj   +1 more source

Fast Convolutional Method for Automatic Sleep Stage Classification [PDF]

Healthcare Informatics Research, 2018
ObjectivesPolysomnography is essential to diagnose sleep disorders. It is used to identify a patient's sleep pattern during sleep. This pattern is obtained by a doctor or health practitioner by using a scoring process, which is time consuming.
Intan Nurma Yulita, Mohamad Ivan Fanany, Aniati Murni Arymurthy   +2 more
doaj   +1 more source

Sleep Stage Classification Using EEG Signal Analysis: A Comprehensive Survey and New Investigation

Entropy, 2016
Sleep specialists often conduct manual sleep stage scoring by visually inspecting the patient’s neurophysiological signals collected at sleep labs. This is, generally, a very difficult, tedious and time-consuming task.
Khald Ali I. Aboalayon, Miad Faezipour, Wafaa S. Almuhammadi, Saeid Moslehpour   +3 more
doaj   +1 more source

Automatic Sleep Stages Classification Using EEG Entropy Features and Unsupervised Pattern Analysis Techniques

Entropy, 2014
Sleep is a growing area of research interest in medicine and neuroscience. Actually, one major concern is to find a correlation between several physiologic variables and sleep stages.
Jose Luis Rodríguez-Sotelo, Alejandro Osorio-Forero, Alejandro Jiménez-Rodríguez, David Cuesta-Frau, Eva Cirugeda-Roldán, Diego Peluffo   +5 more
doaj   +1 more source

Verification for Diagnosis of Sleep-Related Hypoventilation and Carbon Dioxide Partial Pressure During Sleep in Children Using End-Tidal Carbon Dioxide [PDF]

Sleep Medicine Research, 2022
Background and Objective From the past, several researchers have studied and measured the partial pressure of carbon dioxide during sleep in normal children to establish diagnostic criteria for hypoventilation in children.
Jang Gyu Han, Hannah Park, Ji Sun Yang, Ji Su Kim, Bumhee Park, Do-Yang Park, Hyun Jun Kim   +6 more
doaj   +1 more source

Automated sleep stage detection based on recurrence quantification analysis using machine learning [PDF]

Journal of Applied Research on Industrial Engineering, 2022
In recent years, the use of intelligent methods for automatic detection of sleep stages in medical applications to increase diagnostic accuracy and reduce the workload of physicians in analyzing sleep data by visual inspection is one of the important ...
Mohammad Karimi Moridani, Atiye Hajiali
doaj   +1 more source

Sleep EEG Derived From Behind-the-Ear Electrodes (cEEGrid) Compared to Standard Polysomnography: A Proof of Concept Study

Frontiers in Human Neuroscience, 2018
Electroencephalography (EEG) recordings represent a vital component of the assessment of sleep physiology, but the methodology presently used is costly, intrusive to participants, and laborious in application.
Annette Sterr, James K. Ebajemito, Kaare B. Mikkelsen, Maria A. Bonmati-Carrion, Nayantara Santhi, Ciro della Monica, Lucinda Grainger, Giuseppe Atzori, Victoria Revell, Stefan Debener, Stefan Debener, Derk-Jan Dijk, Derk-Jan Dijk, Maarten DeVos   +13 more
doaj   +1 more source

Does Rapid Eye Movement Sleep Aggravate Obstructive Sleep Apnea? [PDF]

Clinical and Experimental Otorhinolaryngology, 2019
Objectives. To investigate the apnea-hypopnea index (AHI) according to the sleep stage in more detail after control of posture. Methods. Patients who underwent nocturnal polysomnography between December 2007 and July 2018 were retrospectively evaluated ...
Sung Hee Kim, Chan Joo Yang, Jong Tae Baek, Sang Min Hyun, Cheon Sik Kim, Sang-Ahm Lee, Yoo-Sam Chung   +6 more
doaj   +1 more source

DeepSleepNet-Lite: A Simplified Automatic Sleep Stage Scoring Model With Uncertainty Estimates [PDF]

, 2021
Luigi Fiorillo, Paolo Favaro, Francesca Dalia Faraci   +2 more
openalex   +2 more sources