AIMC Topic: Sleep Stages

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Classification at the accuracy limit: facing the problem of data ambiguity.

Scientific reports Dec 21, 2022
Data classification, the process of analyzing data and organizing it into categories or clusters, is a fundamental computing task of natural and artificial information processing systems. Both supervised classification and unsupervised clustering wor...
Humans Bayes Theorem Sleep Sleep Stages Neural Networks, Computer Algorithms
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Fast Sleep Stage Classification Using Cascaded Support Vector Machines with Single-Channel EEG Signals.

Sensors (Basel, Switzerland) Dec 16, 2022
Long-term sleep stage monitoring is very important for the diagnosis and treatment of insomnia. With the development of wearable electroencephalogram (EEG) devices, we developed a fast and accurate sleep stage classification method in this study with...
Support Vector Machine Sleep Stages Electroencephalography Signal Processing, Computer-Assisted Sleep
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Sleep Staging Framework with Physiologically Harmonized Sub-Networks.

Methods (San Diego, Calif.) Nov 24, 2022
Sleep screening is an important tool for both healthcare and neuroscientific research. Automatic sleep scoring is an alternative to the time-consuming gold-standard manual scoring procedure. Recently there have seen promising results on automatic sta...
Neural Networks, Computer Electroencephalography Humans Sleep Sleep Stages
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Pediatric Automatic Sleep Staging: A Comparative Study of State-of-the-Art Deep Learning Methods.

IEEE transactions on bio-medical engineering Nov 21, 2022
BACKGROUND: Despite the tremendous prog- ress recently made towards automatic sleep staging in adults, it is currently unknown if the most advanced algorithms generalize to the pediatric population, which displays distinctive characteristics in overn...
Humans Adult Polysomnography Sleep Stages Sleep Apnea, Obstructive Deep Learning Sleep Child
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Automated Analysis of Sleep Study Parameters Using Signal Processing and Artificial Intelligence.

International journal of environmental research and public health Oct 14, 2022
An automated sleep stage categorization can readily face noise-contaminated EEG recordings, just as other signal processing applications. Therefore, the denoising of the contaminated signals is inevitable to ensure a reliable analysis of the EEG sign...
Sleep Stages Signal Processing, Computer-Assisted Sleep Artificial Intelligence Algorithms Electroencephalography
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An Improved Neural Network Based on SENet for Sleep Stage Classification.

IEEE journal of biomedical and health informatics Oct 4, 2022
Sleep staging is an important step in analyzing sleep quality. Traditional manual analysis by psychologists is time-consuming. In this paper, we propose an automatic sleep staging model with an improved attention module and hidden Markov model (HMM)....
Sleep Stages Neural Networks, Computer Electroencephalography Sleep Polysomnography Humans
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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 Stages Sleep Artificial Intelligence Polysomnography 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 Deep Learning Sleep Stages Humans Electroencephalography 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...
Polysomnography Electrooculography Sleep Stages Electroencephalography Humans Signal Processing, Computer-Assisted Machine Learning
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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...
Adult Male Female Reproducibility of Results Humans Observer Variation Algorithms Sleep Stages Deep Learning Sleep
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