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Comparative study of the SleepImage ring device and polysomnography for diagnosing obstructive sleep apnea
Purpose We aim to evaluate the diagnostic performance of the SleepImage Ring device in identifying obstructive sleep apnea (OSA) across different...
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The Comparison Between Fitbit Alta HR and Polysomnography in Monitoring Sleep of Young Adults
As an alternative to Polysomnography (PSG), Fitbit Alta HR (Fitbit) could provide an easier way to monitor sleep. Since the accuracy of Fitbit sleep...
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A Machine Learning Model for Automated Classification of Sleep Stages using Polysomnography Signals
The changes in social rhythm and increase in the pressure in professional sectors cause improper proper sleep on daily basis, which ultimately...
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High-Performance Flexible Microneedle Array as a Low-Impedance Surface Biopotential Dry Electrode for Wearable Electrophysiological Recording and Polysomnography
HighlightsPolyimide-based flexible microneedle array (PI-MNA) electrodes realize high electrical/mechanical performance and are compatible with...
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An Algorithm for Removing Artifacts in Polysomnography Signals
Polysomnography (PSG) is considered the gold standard for sleep disorders diagnosis. However, its signals are difficult to read in the presence of...
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Body Movement Analysis During Sleep Based on Ultra-wideband Communication Channel Impulse Response Measurement
The study introduces an innovative non-invasive method using Ultra-Wideband (UWB) technology for monitoring body movements during sleep. Conducted at...
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Taxonomy for an Automated Sleep Stage Scoring
The mental and physical health of an individual related to sleep, and thus sleep staging is essential to identify sleep-related diseases and...
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A U-Sleep Model for Sleep Staging Using Electrocardiography and Respiration Signals
Recognizing sleep stages has significant clinical relevance for assessing the physical and mental health of people and for treating sleep-related...
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Exploring the Link Between Brain Waves and Sleep Patterns with Deep Learning Manifold Alignment
Medical data are often multi-modal, which are collected from different sources with different formats, such as text, images, and audio. They have...
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Rapid Eye Movement Sleep Behavior Disorder Detection Using Smart Wristbands: A Preliminary Study
In recent years wearable commercial devices, such as smart wrist-bands, have become popular principally for sport activity monitoring. Among them,...
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Sleep Quality in Population Studies – Relationship of BMI and Sleep Quality in Men
Sleep is a physiological state in which quality and quantity should be kept accurate to maintain health in humans. Length of sleep is one of the...
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A Deep Learning Framework for Sleep Apnea Detection
Sleep apnea is a common sleep problem that has a major impact on society. The gold standard, polysomnography, is difficult to obtain, can be...
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An Automated Scoring for REM and N3 Stage Using Wavelet Filters and Support Vector Machine with PSG Signal
Sleep architecture and sleep quality have constantly been engaging topics for sleep researchers. One of the fundamental foundations for any sleep...
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Transformer-Based Contrastive Learning Method for Automated Sleep Stages Classification
Automated sleep stages classification facilitates clinical experts in conducting treatment for sleep disorders, as it is more time-efficient...
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Optimization Technique Used in Biomedical for Qualitative Sleep Analysis
A good sleep is as important as good nutrition. The intangible nature of sleep makes it difficult to measure and can only be assessed on individual’s...
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Sleep Quality Analysis Based on Machine Learning
One third of a person’s life is spent in sleep, sleep is a need of life, and the quality of sleep plays a vital role in human health. With the...
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A Single Channel EEG-Based Algorithm for Neonatal Sleep-Wake Classification
Sleep is categorized as an arrangement of modifications occurring in our body inside our brain, muscles, working its way through our eyes (occipital...
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Development of generalizable automatic sleep staging using heart rate and movement based on large databases
PurposeWith the advancement of deep neural networks in biosignals processing, the performance of automatic sleep staging algorithms has improved...
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Accurate and Interpretable Deep Learning Model for Sleep Staging in Children with Sleep Apnea from Pulse Oximetry
Identification of sleep stages is crucial in the diagnosis of sleep-related disorders but relies on the labor-intensive and manual scoring of...
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Classifying Sleep Stages Automatically in Single-channel Against Multi-channel EEG: A Performance Analysis
Sleep plays a vital part in humans health. The correct classification of sleep stages provides clinical information that can be used to diagnose...