Atrial fibrillation detection on reconstructed photoplethysmography signals collected from a smartwatch using a denoising autoencoder

Photoplethysmography (PPG) signals collected by wearables have been shown to be effective in accurate detection of atrial fibrillation (AF), provided that the data are devoid of motion and noise artifacts (MNA). Many studies have been previously conducted to detect AF arrhythmia using PPG data; howe...

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Veröffentlicht in:	Expert systems with applications Jg. 237; S. 121611
Hauptverfasser:	Mohagheghian, Fahimeh, Han, Dong, Ghetia, Om, Chen, Darren, Peitzsch, Andrew, Nishita, Nishat, Ding, Eric Y., Mensah Otabil, Edith, Noorishirazi, Kamran, Hamel, Alexander, Dickson, Emily L., DiMezza, Danielle, Tran, Khanh-Van, McManus, David D., Chon, Ki H.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.03.2024
Schlagworte:	Atrial fibrillation Autoencoder Deep learning Denoising Photoplethysmography Deep learning Photoplethysmography Autoencoder Atrial fibrillation Denoising
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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