Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning [article]

Maxime Voisin, Yichen Shen, Alireza Aliamiri, Anand Avati, Awni Hannun, Andrew Ng
2018 arXiv   pre-print
We develop an algorithm that accurately detects Atrial Fibrillation (AF) episodes from photoplethysmograms (PPG) recorded in ambulatory free-living conditions. We collect and annotate a dataset containing more than 4000 hours of PPG recorded from a wrist-worn device. Using a 50-layer convolutional neural network, we achieve a test AUC of 95% and show robustness to motion artifacts inherent to PPG signals. Continuous and accurate detection of AF from PPG has the potential to transform consumer
more » ... arable devices into clinically useful medical monitoring tools.
arXiv:1811.07774v2 fatcat:3tdztno5fbd4lhl2vzperitt7e