AIMC Topic: Sleep

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Automated Analysis of Sleep Study Parameters Using Signal Processing and Artificial Intelligence.

International journal of environmental research and public health Oct 14, 2022
An automated sleep stage categorization can readily face noise-contaminated EEG recordings, just as other signal processing applications. Therefore, the denoising of the contaminated signals is inevitable to ensure a reliable analysis of the EEG sign...
Sleep Stages Signal Processing, Computer-Assisted Sleep Algorithms Electroencephalography Artificial Intelligence
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An Improved Neural Network Based on SENet for Sleep Stage Classification.

IEEE journal of biomedical and health informatics Oct 4, 2022
Sleep staging is an important step in analyzing sleep quality. Traditional manual analysis by psychologists is time-consuming. In this paper, we propose an automatic sleep staging model with an improved attention module and hidden Markov model (HMM)....
Humans Sleep Polysomnography Sleep Stages Neural Networks, Computer Electroencephalography
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Sleep classification using Consumer Sleep Technologies and AI: A review of the current landscape.

Sleep medicine Sep 22, 2022
Classifying sleep stages in real-time represents considerable potential, for instance in enabling interactive noise masking in noisy environments when persons are in a state of light sleep or to support clinical staff in analyzing sleep patterns etc....
Sleep Stages Sleep Polysomnography Artificial Intelligence Algorithms Humans
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A review of automated sleep disorder detection.

Computers in biology and medicine Sep 16, 2022
Automated sleep disorder detection is challenging because physiological symptoms can vary widely. These variations make it difficult to create effective sleep disorder detection models which support hu-man experts during diagnosis and treatment monit...
Sleep Wake Disorders Algorithms Sleep Humans Artificial Intelligence Machine Learning
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A Deep Learning Approach to Classify Sitting and Sleep History from Raw Accelerometry Data during Simulated Driving.

Sensors (Basel, Switzerland) Sep 1, 2022
Prolonged sitting and inadequate sleep can impact driving performance. Therefore, objective knowledge of a driver's recent sitting and sleep history could help reduce safety risks. This study aimed to apply deep learning to raw accelerometry data col...
Humans Adult Male Deep Learning Female Young Adult Movement Adolescent Sleep Accelerometry Sitting Position
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Comparison of Eye and Face Features on Drowsiness Analysis.

Sensors (Basel, Switzerland) Aug 30, 2022
Drowsiness is one of the leading causes of traffic accidents. For those who operate large machinery or motor vehicles, incidents due to lack of sleep can cause property damage and sometimes lead to grave consequences of injuries and fatality. This st...
Humans Neural Networks, Computer Cluster Analysis Accidents, Traffic Attention Sleep
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A systematic review of deep learning methods for modeling electrocardiograms during sleep.

Physiological measurement Aug 12, 2022
Sleep is one of the most important human physiological activities, and plays an essential role in human health. Polysomnography (PSG) is the gold standard for measuring sleep quality and disorders, but it is time-consuming, labor-intensive, and prone...
Electrocardiography Sleep Apnea Syndromes Polysomnography Sleep Humans Deep Learning
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SleepFCN: A Fully Convolutional Deep Learning Framework for Sleep Stage Classification Using Single-Channel Electroencephalograms.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jul 29, 2022
Sleep is a vital process of our daily life as we roughly spend one-third of our lives asleep. In order to evaluate sleep quality and potential sleep disorders, sleep stage classification is a gold standard method. In this paper, we introduce a novel ...
Sleep Deep Learning Humans Sleep Stages Electroencephalography Neural Networks, Computer
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A Hybrid Expert System for Individualized Quantification of Electrical Status Epilepticus During Sleep Using Biogeography-Based Optimization.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jul 19, 2022
Electrical status epilepticus during sleep (ESES) is an epileptic encephalopathy in children with complex clinical manifestations. It is accompanied by specific electroencephalography (EEG) patterns of continuous spike and slow-waves. Quantifying suc...
Electroencephalography Sleep China Child Humans Expert Systems Reproducibility of Results Status Epilepticus
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Waveform detection by deep learning reveals multi-area spindles that are selectively modulated by memory load.

eLife Jun 29, 2022
Sleep is generally considered to be a state of large-scale synchrony across thalamus and neocortex; however, recent work has challenged this idea by reporting isolated sleep rhythms such as slow oscillations and spindles. What is the spatial scale of...
Memory Electrocorticography Electroencephalography Sleep Animals Deep Learning
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