Deep Attention Networks With Multi-Temporal Information Fusion for Sleep Apnea Detection

Deep Attention Networks With Multi-Temporal Information Fusion for Sleep Apnea Detection

Sleep Apnea (SA) is a prevalent sleep disorder with multifaceted etiologies that can have severe consequences for patients. Diagnosing SA traditionally relies on the in-laboratory polysomnogram (PSG), which records various human physiological activities overnight. SA diagnosis involves manual scorin...

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Bibliographic Details
Main Authors: Meng Jiao, Changyue Song, Xiaochen Xian, Shihao Yang, Feng Liu
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Journal of Engineering in Medicine and Biology
Subjects:
Sleep apnea (SA)
electrocardiogram
deep learning
convolutional neural network (CNN)
multi-head attention
Online Access:https://ieeexplore.ieee.org/document/10539178/
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https://ieeexplore.ieee.org/document/10539178/

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