Contribution of Different Subbands of ECG in Sleep Apnea Detection Evaluated Using Filter Bank Decomposition and a Convolutional Neural Network

A variety of feature extraction and classification approaches have been proposed using electrocardiogram (ECG) and ECG-derived signals for improving the performance of detecting apnea events and diagnosing patients with obstructive sleep apnea (OSA). The purpose of this study is to further evaluate...

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Detalles Bibliográficos
Autores principales: Yeh, Cheng-Yu, Chang, Hung-Yu, Hu, Jiy-Yao, Lin, Chun-Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8777653/
https://www.ncbi.nlm.nih.gov/pubmed/35062470
http://dx.doi.org/10.3390/s22020510

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8777653/
https://www.ncbi.nlm.nih.gov/pubmed/35062470
http://dx.doi.org/10.3390/s22020510

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