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Sleep

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Analysing the predictive capacity and dose-response of wellness in load monitoring.

Journal of sports sciences
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...

DeepSleep convolutional neural network allows accurate and fast detection of sleep arousal.

Communications biology
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 Neural Network Sleep Scoring Using Combined Motion and Heart Rate Variability Data.

Sensors (Basel, Switzerland)
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 ...

Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning.

Cell
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...

Automatic sleep scoring: A deep learning architecture for multi-modality time series.

Journal of neuroscience methods
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...

Can pre-trained convolutional neural networks be directly used as a feature extractor for video-based neonatal sleep and wake classification?

BMC research notes
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...

Sleep-Dependent Memory Consolidation in a Neuromorphic Nanowire Network.

ACS applied materials & interfaces
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...

Sleep stage classification for child patients using DeConvolutional Neural Network.

Artificial intelligence in medicine
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...

Effects on sleep from group activity with a robotic seal for nursing home residents with dementia: a cluster randomized controlled trial.

International psychogeriatrics
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...