AIMC Topic: Sleep Stages

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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....
Humans Sleep Polysomnography Sleep Stages Artificial Intelligence Algorithms
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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 Sleep Stages Deep Learning Electroencephalography Humans Neural Networks, Computer
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A multi-modal assessment of sleep stages using adaptive Fourier decomposition and machine learning.

Computers in biology and medicine Jul 14, 2022
Healthy sleep is essential for the rejuvenation of the body and helps in maintaining good health. Many people suffer from sleep disorders that are characterized by abnormal sleep patterns. Automated assessment of such disorders using biomedical signa...
Sleep Stages Humans Machine Learning Polysomnography Electroencephalography Electrooculography Signal Processing, Computer-Assisted
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Validation Study on Automated Sleep Stage Scoring Using a Deep Learning Algorithm.

Medicina (Kaunas, Lithuania) Jun 9, 2022
Polysomnography is manually scored by sleep experts. However, manual scoring is a time-consuming and labor-intensive task. The goal of this study was to verify the accuracy of automated sleep-stage scoring based on a deep learning algorithm compared...
Humans Algorithms Adult Male Female Reproducibility of Results Observer Variation Sleep Stages Deep Learning Sleep
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A Deep Learning Method Approach for Sleep Stage Classification with EEG Spectrogram.

International journal of environmental research and public health May 23, 2022
The classification of sleep stages is an important process. However, this process is time-consuming, subjective, and error-prone. Many automated classification methods use electroencephalogram (EEG) signals for classification. These methods do not cl...
Sleep Sleep Stages Neural Networks, Computer Deep Learning Electroencephalography
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Sleep staging classification based on a new parallel fusion method of multiple sources signals.

Physiological measurement Apr 28, 2022
In the field of medical informatics, sleep staging is a challenging and time consuming task undertaken by sleep experts. The conventional method for sleep staging is to analyze Polysomnograms (PSGs) recorded in a sleep lab, but the sleep monitoring w...
Sleep Stages Sleep Electrooculography Support Vector Machine Electroencephalography Humans Algorithms
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Polysomnographic identification of anxiety and depression using deep learning.

Journal of psychiatric research Mar 24, 2022
Anxiety and depression are common psychiatric conditions associated with significant morbidity and healthcare costs. Sleep is an evolutionarily conserved health state. Anxiety and depression have a bidirectional relationship with sleep. This study re...
Depression Polysomnography Sleep Stages Anxiety Deep Learning Humans
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Automatic sleep stage classification: A light and efficient deep neural network model based on time, frequency and fractional Fourier transform domain features.

Artificial intelligence in medicine Mar 9, 2022
This work proposed a novel method for automatic sleep stage classification based on the time, frequency, and fractional Fourier transform (FRFT) domain features extracted from a single-channel electroencephalogram (EEG). Bidirectional long short-term...
Sleep Stages Sleep Neural Networks, Computer Fourier Analysis Electroencephalography
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A Deep Shared Multi-Scale Inception Network Enables Accurate Neonatal Quiet Sleep Detection With Limited EEG Channels.

IEEE journal of biomedical and health informatics Mar 7, 2022
In this paper, we introduce a new variation of the Convolutional Neural Network Inception block, called Sinc, for sleep stage classification in premature newborn babies using electroencephalogram (EEG). In practice, there are many medical centres whe...
Humans Sleep Sleep Stages Infant, Newborn Neural Networks, Computer Electroencephalography Algorithms
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Convolutional neural network is a good technique for sleep staging based on HRV: A comparative analysis.

Neuroscience letters Feb 25, 2022
The fluctuation of heart rate is regulated by autonomic nervous system. In human sleep, the autonomic nervous system plays a leading role. Therefore, we can use heart-rate variability (HRV) to stage the sleep process. Based on two independent public ...
Sleep Stages Sleep, REM Humans Heart Rate Neural Networks, Computer Sleep
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