Results 21 to 30 of about 155,892 (263)

Sleep Track: Automated Detection and Classification of Sleep Stages [PDF]

E3S Web of Conferences, 2023
Sleep is vital for our body’s physical restoration, but sleep disorders can cause various problems. Determining sleep stages is essential for diagnosing and curing such disorders.
Ram Kumar R.P., Rithesh A., Josh Pranav, Karthik Raj B., John Vivek, Shiva Prasad Doma   +5 more
doaj   +1 more source

HARU Sleep: A Deep Learning-Based Sleep Scoring System With Wearable Sheet-Type Frontal EEG Sensors

IEEE Access, 2022
Analysis of sleep stages using electroencephalograms (EEGs), a critical procedure in health monitoring, has been researched extensively. Scoring of the sleep stages is highly dependent on experts’ knowledge or hand-crafted features created by ...
Shoya Matsumori, Kosei Teramoto, Hiroya Iyori, Takanori Soda, Shusuke Yoshimoto, Haruo Mizutani   +5 more
doaj   +1 more source

A Review of Cerebral Hemodynamics During Sleep Using Near-Infrared Spectroscopy

Frontiers in Neurology, 2020
Investigating cerebral hemodynamic changes during regular sleep cycles and sleep disorders is fundamental to understanding the nature of physiological and pathological mechanisms in the regulation of cerebral oxygenation during sleep.
Haoran Ren, Xinyu Jiang, Ke Xu, Chen Chen, Yafei Yuan, Chenyun Dai, Wei Chen, Wei Chen, Wei Chen   +8 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 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

Sleep stage detection using only heart rate

Health Informatics Journal, 2020
Getting enough quality sleep plays a vital role in protecting our mental health, physical health, and quality of life. Sleep deprivation can make it difficult to concentrate on daily activities, and lower sleep quality is associated with hypertension ...
Yasue Mitsukura, Koichi Fukunaga, Masato Yasui, Masaru Mimura   +3 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

Comparison of sleep in hypothyroid patients with normal controls

National Journal of Physiology, Pharmacy and Pharmacology, 2017
Background: Sleep - A complex amalgam of behavioral and electrophysiological process is maintained by organized interaction between neurons, neural circuits, and neurotransmitters.
Kavitha Sivaprakasam, Shanthimalar Ramamoorthy   +1 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

Employing a Convolutional Neural Network to Classify Sleep Stages from EEG Signals Using Feature Reduction Techniques

Algorithms
One of the most essential components of human life is sleep. One of the first steps in spotting abnormalities connected to sleep is classifying sleep stages.
Maadh Rajaa Mohammed, Ali Makki Sagheer
doaj   +1 more source