AIMC Topic: Sleep

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Sleep-Dependent Memory Consolidation in a Neuromorphic Nanowire Network.

ACS applied materials & interfaces Nov 2, 2020
A neuromorphic network composed of silver nanowires coated with TiO is found to show certain parallels with neural networks in nature such as biological brains. Owing to the memristive properties emerging at nanowire-to-nanowire contacts, where the A...
Humans Neural Networks, Computer Sleep Surface Properties Nanowires Memory Consolidation Particle Size Titanium Silver
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Sleep stage classification for child patients using DeConvolutional Neural Network.

Artificial intelligence in medicine Nov 2, 2020
Studies from the literature show that the prevalence of sleep disorder in children is far higher than that in adults. Although much research effort has been made on sleep stage classification for adults, children have significantly different characte...
Sleep Stages Electroencephalography Sleep Polysomnography Humans Child, Preschool Child Neural Networks, Computer Aged
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Effects on sleep from group activity with a robotic seal for nursing home residents with dementia: a cluster randomized controlled trial.

International psychogeriatrics Sep 28, 2020
OBJECTIVES: Sleep disturbances are common in people with dementia and increase with the severity of the disease. Sleep disturbances are complex and caused by several factors and are difficult to treat. There is a need for more robust and systematic s...
Sleep Nursing Homes Dementia Humans Robotics Aged Robotic Surgical Procedures Quality of Life
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The effect of a social robot intervention on sleep and motor activity of people living with dementia and chronic pain: A pilot randomized controlled trial.

Maturitas Sep 24, 2020
OBJECTIVE: To investigate the effect of a social robot intervention on sleep and motor activity in nursing home residents living with dementia and chronic pain.
Aged, 80 and over Male Pilot Projects Humans Female Aged Sleep Nursing Homes Motor Activity Chronic Pain Dementia Australia Robotics
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Discriminating between sleep and exercise-induced fatigue using computer vision and behavioral genetics.

Journal of neurogenetics Aug 19, 2020
Following prolonged swimming, cycle between active swimming bouts and inactive quiescent bouts. Swimming is exercise for and here we suggest that inactive bouts are a recovery state akin to fatigue. It is known that cGMP-dependent kinase (PKG) acti...
Cyclic GMP-Dependent Protein Kinases Genetics, Behavioral Movement Caenorhabditis elegans Physical Exertion Caenorhabditis elegans Proteins Pharynx Sleep Lab-On-A-Chip Devices Animals Artificial Intelligence Rest Fatigue Aging Swimming Biomechanical Phenomena Escherichia coli
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Photoplethysmographic-based automated sleep-wake classification using a support vector machine.

Physiological measurement Aug 11, 2020
OBJECTIVE: Sleep quality has a significant impact on human mental and physical health. The detection of sleep-wake states is thus of paramount importance in the study of sleep. The gold standard method for sleep-wake classification is multi-sensor-ba...
Algorithms Wearable Electronic Devices Photoplethysmography Support Vector Machine Sleep Polysomnography Humans
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Prediction and classification of sleep quality based on phase synchronization related whole-brain dynamic connectivity using resting state fMRI.

NeuroImage Jul 22, 2020
Recently, functional network connectivity (FNC) has been extended from static to dynamic analysis to explore the time-varying functional organization of brain networks. Nowadays, a majority of dynamic FNC (dFNC) analysis frameworks identified recurri...
Support Vector Machine Magnetic Resonance Imaging Sleep Datasets as Topic Cerebral Cortex Connectome Humans Nerve Net Adult Models, Theoretical
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Neonatal EEG sleep stage classification based on deep learning and HMM.

Journal of neural engineering Jun 25, 2020
OBJECTIVE: Automatic sleep stage scoring is of great importance for investigating sleep architecture during infancy. In this work, we introduce a novel multichannel approach based on deep learning networks and hidden Markov models (HMM) to improve th...
Infant, Newborn Infant Signal Processing, Computer-Assisted Sleep Sleep Stages Humans Deep Learning Electroencephalography
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Application of deep learning to improve sleep scoring of wrist actigraphy.

Sleep medicine May 15, 2020
BACKGROUND: Estimation of sleep parameters by wrist actigraphy is highly dependent on performance of the interpretative algorithm (IA) that converts movement data into sleep/wake scores.
Actigraphy Polysomnography Deep Learning Humans Wrist Female Sleep Adult
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Automatic snoring sounds detection from sleep sounds based on deep learning.

Physical and engineering sciences in medicine May 6, 2020
Snoring is a typical characteristic of obstructive sleep apnea hypopnea syndrome (OSAHS) and can be used for its diagnosis. The purpose of this paper is to develop an automatic snoring detection algorithm for classifying snore and non-snore sound seg...
Deep Learning ROC Curve Sleep Adult Male Middle Aged Automation Snoring Humans Neural Networks, Computer Algorithms Female
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