AIMC Topic: Sleep Stages

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Automated sleep state classification of wide-field calcium imaging data via multiplex visibility graphs and deep learning.

Journal of neuroscience methods Nov 22, 2021
BACKGROUND: Wide-field calcium imaging (WFCI) allows for monitoring of cortex-wide neural dynamics in mice. When applied to the study of sleep, WFCI data are manually scored into the sleep states of wakefulness, non-REM (NREM) and REM by use of adjun...
Animals Deep Learning Mice Reproducibility of Results Wakefulness Sleep Sleep Stages Electroencephalography Calcium
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Inter-database validation of a deep learning approach for automatic sleep scoring.

PloS one Aug 16, 2021
STUDY OBJECTIVES: Development of inter-database generalizable sleep staging algorithms represents a challenge due to increased data variability across different datasets. Sharing data between different centers is also a problem due to potential restr...
Deep Learning Polysomnography Electroencephalography Sleep Humans Algorithms Sleep Stages Databases, Factual Neural Networks, Computer
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Detailed Assessment of Sleep Architecture With Deep Learning and Shorter Epoch-to-Epoch Duration Reveals Sleep Fragmentation of Patients With Obstructive Sleep Apnea.

IEEE journal of biomedical and health informatics Jul 27, 2021
Traditional sleep staging with non-overlapping 30-second epochs overlooks multiple sleep-wake transitions. We aimed to overcome this by analyzing the sleep architecture in more detail with deep learning methods and hypothesized that the traditional s...
Sleep Stages Deep Learning Sleep Apnea, Obstructive Sleep Humans Polysomnography Sleep Deprivation
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Cross-Gram matrices and their use in transfer learning: Application to automatic REM detection using heart rate.

Computer methods and programs in biomedicine Jul 21, 2021
BACKGROUND AND OBJECTIVES: while traditional sleep staging is achieved through the visual - expert-based - annotation of a polysomnography, it has the disadvantages of being unpractical and expensive. Alternatives have been developed over the years t...
Humans Machine Learning Heart Rate Polysomnography Sleep Stages
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A deep learning algorithm for sleep stage scoring in mice based on a multimodal network with fine-tuning technique.

Neuroscience research Jul 17, 2021
Sleep stage scoring is important to determine sleep structure in preclinical and clinical research. The aim of this study was to develop an automatic sleep stage classification system for mice with a new deep neural network algorithm. For the purpose...
Algorithms Animals Deep Learning Sleep Mice Sleep Stages Electroencephalography
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Automated scoring of pre-REM sleep in mice with deep learning.

Scientific reports Jun 10, 2021
Reliable automation of the labor-intensive manual task of scoring animal sleep can facilitate the analysis of long-term sleep studies. In recent years, deep-learning-based systems, which learn optimal features from the data, increased scoring accurac...
Sleep Stages Sleep, REM Deep Learning Mice Sleep Polysomnography Models, Theoretical Algorithms Animals
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Real-time, automatic, open-source sleep stage classification system using single EEG for mice.

Scientific reports May 27, 2021
We developed a real-time sleep stage classification system with a convolutional neural network using only a one-channel electro-encephalogram source from mice and universally available features in any time-series data: raw signal, spectrum, and zeitg...
Animals Mice Electroencephalography Electrodes Signal Processing, Computer-Assisted Neural Networks, Computer Sleep Stages Electromyography Algorithms Superficial Back Muscles
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Machine learning prediction of sleep stages in dairy cows from heart rate and muscle activity measures.

Scientific reports May 25, 2021
Sleep is important for cow health and shows promise as a tool for assessing welfare, but methods to accurately distinguish between important sleep stages are difficult and impractical to use with cattle in typical farm environments. The objective of ...
Myocardium Models, Biological Polysomnography Sleep Stages Heart Rate Animals Cattle ROC Curve Neural Networks, Computer Machine Learning
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Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning.

IEEE transactions on bio-medical engineering May 21, 2021
BACKGROUND: Despite recent significant progress in the development of automatic sleep staging methods, building a good model still remains a big challenge for sleep studies with a small cohort due to the data-variability and data-inefficiency issues....
Polysomnography Sleep Stages Humans Machine Learning Sleep Neural Networks, Computer
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A CNN identified by reinforcement learning-based optimization framework for EEG-based state evaluation.

Journal of neural engineering May 18, 2021
Electroencephalogram (EEG) data, as a kind of complex time-series, is one of the most widely-used information measurements for evaluating human psychophysiological states. Recently, numerous works applied deep learning techniques, especially the conv...
Sleep Stages Algorithms Humans Electroencephalography Neural Networks, Computer Sleep
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