AIMC Topic: Sleep Stages

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Automated sleep stage scoring of the Sleep Heart Health Study using deep neural networks.

Sleep Oct 21, 2019
STUDY OBJECTIVES: Polysomnography (PSG) scoring is labor intensive and suffers from variability in inter- and intra-rater reliability. Automated PSG scoring has the potential to reduce the human labor costs and the variability inherent to this task. ...
Humans Neural Networks, Computer Reproducibility of Results Polysomnography Electrooculography Sleep Stages Electroencephalography Electromyography Deep Learning
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Automatic Sleep Stages Classification Combining Semantic Representation and Dynamic Expert System.

Studies in health technology and informatics Aug 21, 2019
Interest in sleep has been growing in the last decades, considering its benefits for well-being, but also to diagnose sleep troubles. The gold standard to monitor sleep consists of recording the course of many physiological parameters during a whole ...
Polysomnography Sleep Stages Humans Expert Systems Semantics Electroencephalography
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Deep Learning with Convolutional Neural Network for detecting microsleep states from EEG: A comparison between the oversampling technique and cost-based 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, 2019
Any occupation which involves critical decision making in real-time requires attention and concentration. When repetitive and expanded working periods are encountered, it can result in microsleeps. Microsleeps are complete lapses in which a subject i...
Humans Electroencephalography Attention Sleep Stages Neural Networks, Computer Deep Learning
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Fusion of End-to-End Deep Learning Models for Sequence-to-Sequence Sleep Staging.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Sleep staging, a process of identifying the sleep stages associated with polysomnography (PSG) epochs, plays an important role in sleep monitoring and diagnosing sleep disorders. We present in this work a model fusion approach to automate this task. ...
Deep Learning Polysomnography Sleep Stages Humans Sleep Wake Disorders Computer Simulation
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Comparison of support vector machines based on particle swarm optimization and genetic algorithm in sleep staging.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2019
BACKGROUND: Heart rate variability (HRV) can reflect the relationship between heart rhythm and sleep structure.
Heart Rate Sleep Stages Electrocardiography Support Vector Machine Humans Biomarkers Computer Simulation Algorithms
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Expert-level sleep scoring with deep neural networks.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2018
OBJECTIVES: Scoring laboratory polysomnography (PSG) data remains a manual task of visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb movements. Attempts to automate this process have been hampered by the com...
Sleep Stages Datasets as Topic Classification Polysomnography Models, Biological Sleep Humans Neural Networks, Computer Machine Learning Electroencephalography Sleep Apnea Syndromes
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Automatic Sleep Stage Classification Using Single-Channel EEG: Learning Sequential Features with Attention-Based Recurrent Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
We propose in this work a feature learning approach using deep bidirectional recurrent neural networks (RNNs) with attention mechanism for single-channel automatic sleep stage classification. We firstly decompose an EEG epoch into multiple small fram...
Humans Sleep Stages Electroencephalography Neural Networks, Computer
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A Two Stage Approach for the Automatic Detection of Insomnia.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Chronic insomnia can significantly impair an individual's quality of life leading to a high societal cost. Unfortunately, limited automated tools exist that can assist clinicians in the timely detection of insomnia. In this paper, we propose a two st...
Middle Aged Adolescent Support Vector Machine Neural Networks, Computer Sensitivity and Specificity Sleep Initiation and Maintenance Disorders Female Male Humans Normal Distribution Young Adult Discriminant Analysis Sleep Stages Aged Adult Electroencephalography
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DNN Filter Bank Improves 1-Max Pooling CNN for Single-Channel EEG Automatic Sleep Stage Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
We present in this paper an efficient convolutional neural network (CNN) running on time-frequency image features for automatic sleep stage classification. Opposing to deep architectures which have been used for the task, the proposed CNN is much sim...
Algorithms Electroencephalography Sleep Stages Humans Neural Networks, Computer
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Interactive Sleep Stage Labelling Tool For Diagnosing Sleep Disorder Using 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, 2018
Traditional manual scoring of the entire sleep for diagnosis of sleep disorders is highly time-consuming and dependent to experts experience. Thus, automatic methods based on electrooculography (EOG) analysis have been increasingly attracted attentio...
Humans Diagnosis, Computer-Assisted Electroencephalography Electromyography Deep Learning Sleep Wake Disorders Electrooculography Sleep Sleep Stages Polysomnography
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