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Sleep

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Discriminating between sleep and exercise-induced fatigue using computer vision and behavioral genetics.

Journal of neurogenetics
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...

Photoplethysmographic-based automated sleep-wake classification using a support vector machine.

Physiological measurement
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...

Prediction and classification of sleep quality based on phase synchronization related whole-brain dynamic connectivity using resting state fMRI.

NeuroImage
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...

Neonatal EEG sleep stage classification based on deep learning and HMM.

Journal of neural engineering
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...

Application of deep learning to improve sleep scoring of wrist actigraphy.

Sleep medicine
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.

Automatic snoring sounds detection from sleep sounds based on deep learning.

Physical and engineering sciences in medicine
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...

Automatic detection of cortical arousals in sleep and their contribution to daytime sleepiness.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Significant interscorer variability is found in manual scoring of arousals in polysomnographic recordings (PSGs). We propose a fully automatic method, the Multimodal Arousal Detector (MAD), for detecting arousals.

Addressing database variability in learning from medical data: An ensemble-based approach using convolutional neural networks and a case of study applied to automatic sleep scoring.

Computers in biology and medicine
In this work we examine some of the problems associated with the development of machine learning models with the objective to achieve robust generalization capabilities on common-task multiple-database scenarios. Referred to as the "database variabil...

A Deep Learning Approach for Automated Sleep-Wake Scoring in Pre-Clinical Animal Models.

Journal of neuroscience methods
BACKGROUND: Experimental investigation of sleep-wake dynamics in animals is an important part of pharmaceutical development. Typically, it involves recording of electroencephalogram, electromyogram, locomotor activity, and electrooculogram. Visual id...