Seizure-related differences in biosignal 24-h modulation patterns
A seizure likelihood biomarker could improve seizure monitoring and facilitate adjustment of
treatments based on seizure risk. Here, we tested differences in patient-specific 24-h …
treatments based on seizure risk. Here, we tested differences in patient-specific 24-h …
Automatic sleep-arousal detection with single-lead EEG using stacking ensemble learning
YR Chien, CH Wu, HW Tsao - Sensors, 2021 - mdpi.com
Poor-quality sleep substantially diminishes the overall quality of life. It has been shown that
sleep arousal serves as a good indicator for scoring sleep quality. However, patients are …
sleep arousal serves as a good indicator for scoring sleep quality. However, patients are …
Automatic sleep stage scoring with single-channel EEG using convolutional neural networks
We used convolutional neural networks (CNNs) for automatic sleep stage scoring based on
single-channel electroencephalography (EEG) to learn task-specific filters for classification …
single-channel electroencephalography (EEG) to learn task-specific filters for classification …
Performance evaluation of an automated single-channel sleep–wake detection algorithm
Background A need exists, from both a clinical and a research standpoint, for objective sleep
measurement systems that are both easy to use and can accurately assess sleep and wake …
measurement systems that are both easy to use and can accurately assess sleep and wake …
End-to-end sleep staging using convolutional neural network in raw single-channel EEG
Objective Manual sleep staging on overnight polysomnography (PSG) is time-consuming
and laborious. This study aims to develop an end-to-end automatic sleep staging method in …
and laborious. This study aims to develop an end-to-end automatic sleep staging method in …
Automatic EEG classification: a path to smart and connected sleep interventions
A Khojandi, O Shylo, M Zokaeinikoo - Annals of Operations Research, 2019 - Springer
We develop a random forest classifier to automatically classify brain waves into sleep stages
by using the publicly available data from PhysioBank. More specifically, we use the EEG …
by using the publicly available data from PhysioBank. More specifically, we use the EEG …
[HTML][HTML] Neuroscience from the comfort of your home: Repeated, self-administered wireless dry EEG measures brain function with high fidelity
Recent advances have enabled the creation of wireless,'dry'electroencephalography (EEG)
recording systems, and easy-to-use engaging tasks, that can be operated repeatedly by …
recording systems, and easy-to-use engaging tasks, that can be operated repeatedly by …
Artificial intelligence in sleep medicine: background and implications for clinicians
Polysomnography remains the cornerstone of objective testing in sleep medicine and results
in massive amounts of electrophysiological data, which is well-suited for analysis with …
in massive amounts of electrophysiological data, which is well-suited for analysis with …
Automatic sleep stage classification based on subthalamic local field potentials
Y Chen, C Gong, H Hao, Y Guo, S Xu… - … on Neural Systems …, 2019 - ieeexplore.ieee.org
Deep brain stimulation (DBS) is an established treatment for patients with Parkinson's
disease (PD). Sleep disorders are common complications of PD and affected by subthalamic …
disease (PD). Sleep disorders are common complications of PD and affected by subthalamic …
Quantitative evaluation of EEG-biomarkers for prediction of sleep stages
Electroencephalography (EEG) is immediate and sensitive to neurological changes
resulting from sleep stages and is considered a computing tool for understanding the …
resulting from sleep stages and is considered a computing tool for understanding the …