AIMC Topic: Sleep

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Classification of Sleep-Wake State in Ballistocardiogram system based on Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Sleep state classification is essential for managing and comprehending sleep patterns, and it is usually the first step in identifying sleep disorders. Polysomnography (PSG), the gold standard, is intrusive and inconvenient for regular/long-term slee...
Humans Deep Learning Sleep Wake Disorders Ballistocardiography Sleep Polysomnography
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Self-Organizing Maps for Contrastive Embeddings of Sleep Recordings.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Nowadays, high amounts of data can be acquired in various applications, spurring the need for interpretable data representations that provide actionable insights. Algorithms that yield such representations ideally require as little a priori knowledge...
Sleep Sleep Wake Disorders Humans Neural Networks, Computer Algorithms Learning
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The effect of robot interventions on sleep in adults: a systematic review and network meta-analysis.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine Jul 1, 2022
STUDY OBJECTIVES: Robotic pets or companion robots have demonstrated positive effects on several emotional and physiological factors in humans. Robots could constitute a complementary or alternative method to treat sleep problems, but individual stud...
Humans Aged Robotics Sleep Play and Playthings Network Meta-Analysis Randomized Controlled Trials as Topic
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A deep learning algorithm based on 1D CNN-LSTM for automatic sleep staging.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2022
BACKGROUND: Sleep staging is an important part of sleep research. Traditional automatic sleep staging based on machine learning requires extensive feature extraction and selection.
Algorithms Deep Learning Humans Neural Networks, Computer Sleep Stages Electroencephalography Sleep
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[The accuracy and influencing factors of sleep staging based on single-channel EEG via a deep neural network].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery Dec 7, 2021
To investigate theaccuracy of artificial intelligence sleep staging model in patients with habitual snoring and obstructive sleep apnea hypopnea syndrome (OSAHS) based on single-channel EEG collected from different locations of the head. The clinic...
Middle Aged Electroencephalography Sleep Sleep Stages Adult Male Female Young Adult Humans Artificial Intelligence Retrospective Studies Neural Networks, Computer
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Investigation of Machine Learning and Deep Learning Approaches for Detection of Mild Traumatic Brain Injury from Human Sleep Electroencephalogram.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Traumatic Brain Injury (TBI) is a highly prevalent and serious public health concern. Most cases of TBI are mild in nature, yet some individuals may develop following-up persistent disability. The pathophysiologic causes for those with persistent pos...
Brain Concussion Electroencephalography Sleep Humans Machine Learning Deep Learning
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Efficient J Peak Detection From Ballistocardiogram Using Lightweight Convolutional Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Ballistocardiagram (BCG) is a non-contact and non-invasive technique to obtain physiological information with the potential to monitor Cardio Vascular Disease (CVD) at home. Accurate detection of J-peak is the key to get critical indicators from BCG ...
Neural Networks, Computer Electrocardiography Sleep Ballistocardiography Humans
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LightSleepNet: A Lightweight Deep Model for Rapid Sleep Stage Classification with Spectrograms.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Deep learning has achieved unprecedented success in sleep stage classification tasks, which starts to pave the way for potential real-world applications. However, due to its enormous size, deployment of deep neural networks is hindered by high cost a...
Sleep Stages Electroencephalography Sleep Neural Networks, Computer Deep Learning
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Replay in Deep Learning: Current Approaches and Missing Biological Elements.

Neural computation Oct 12, 2021
Replay is the reactivation of one or more neural patterns that are similar to the activation patterns experienced during past waking experiences. Replay was first observed in biological neural networks during sleep, and it is now thought to play a cr...
Sleep Hippocampus Reinforcement, Psychology Animals Deep Learning Neural Networks, Computer Algorithms
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Assessment of obstructive sleep apnea-related sleep fragmentation utilizing deep learning-based sleep staging from photoplethysmography.

Sleep Oct 11, 2021
STUDY OBJECTIVES: To assess the relationship between obstructive sleep apnea (OSA) severity and sleep fragmentation, accurate differentiation between sleep and wakefulness is needed. Sleep staging is usually performed manually using electroencephalog...
Sleep Apnea, Obstructive Sleep Deep Learning Photoplethysmography Polysomnography Sleep Deprivation Humans
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