AIMC Topic: Sleep

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Machine learning approaches reveal subtle differences in breathing and sleep fragmentation in -derived astrocytes ablated mice.

Journal of neurophysiology Jan 27, 2021
Modern neurophysiology research requires the interrogation of high-dimensionality data sets. Machine learning and artificial intelligence (ML/AI) workflows have permeated into nearly all aspects of daily life in the developed world but have not been ...
Electroencephalography Workflow Sleep Plethysmography Neurophysiology Respiration Homeodomain Proteins Mice Genotype Transcription Factors Astrocytes Machine Learning Animals Gene Expression Profiling
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Analyzing Description, User Understanding and Expectations of AI in Mobile Health Applications.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Previous research has studied medical professionals' perception of artificial intelligence (AI). However, there has been a limited understanding of how healthcare consumers perceive and use AI-powered technologies such as mobile health apps. We colle...
User-Computer Interface Mobile Applications Feedback Health Promotion Communication Humans Motivation Telemedicine Exercise Sleep Artificial Intelligence Consumer Behavior Mental Health
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Authors' response to Atee et al.

Maturitas Jan 14, 2021
Robotics Sleep Motor Activity Chronic Pain Humans Pilot Projects Dementia Social Interaction
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Analysing the predictive capacity and dose-response of wellness in load monitoring.

Journal of sports sciences Jan 6, 2021
This study aimed to identify the predictive capacity of wellness questionnaires on measures of training load using machine learning methods. The distributions of, and dose-response between, wellness and other load measures were also examined, offerin...
Perception Fatigue Sports Soccer Sleep Affect Physical Conditioning, Human Machine Learning Myalgia Football Wearable Electronic Devices Geographic Information Systems Cricket Sport Motivation Surveys and Questionnaires Health Status Decision Trees Stress, Psychological Regression Analysis Physical Exertion Humans
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Comments on Pu et al. (2021), "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 Jan 6, 2021
Dementia Robotics Sleep Motor Activity Humans Pilot Projects Chronic Pain Social Interaction
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DeepSleep convolutional neural network allows accurate and fast detection of sleep arousal.

Communications biology Jan 4, 2021
Sleep arousals are transient periods of wakefulness punctuated into sleep. Excessive sleep arousals are associated with symptoms such as sympathetic activation, non-restorative sleep, and daytime sleepiness. Currently, sleep arousals are mainly annot...
Deep Learning Sleep Polysomnography Arousal Humans
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Deep Neural Network Sleep Scoring Using Combined Motion and Heart Rate Variability Data.

Sensors (Basel, Switzerland) Dec 23, 2020
Performance of wrist actigraphy in assessing sleep not only depends on the sensor technology of the actigraph hardware but also on the attributes of the interpretative algorithm (IA). The objective of our research was to improve assessment of sleep ...
Heart Rate Sleep Actigraphy Humans Polysomnography Neural Networks, Computer Female Male
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Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning.

Cell Dec 16, 2020
Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which ha...
Humans Machine Learning Algorithms Behavior, Animal Wakefulness Mice, Inbred C57BL Linear Models Protein Binding Binding Sites Brain Kinetics Sleep HEK293 Cells Mice Directed Molecular Evolution Animals Amino Acid Sequence Amygdala Serotonin Serotonin Plasma Membrane Transport Proteins Photons
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Automatic sleep scoring: A deep learning architecture for multi-modality time series.

Journal of neuroscience methods Nov 4, 2020
BACKGROUND: Sleep scoring is an essential but time-consuming process, and therefore automatic sleep scoring is crucial and urgent to help address the growing unmet needs for sleep research. This paper aims to develop a versatile deep-learning archite...
Humans Deep Learning Sleep Stages Sleep Electroencephalography Polysomnography
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Can pre-trained convolutional neural networks be directly used as a feature extractor for video-based neonatal sleep and wake classification?

BMC research notes Nov 4, 2020
OBJECTIVE: In this paper, we propose to evaluate the use of pre-trained convolutional neural networks (CNNs) as a features extractor followed by the Principal Component Analysis (PCA) to find the best discriminant features to perform classification u...
Humans Support Vector Machine Sleep Neural Networks, Computer Video Recording Algorithms Infant, Newborn
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