Can smartwatch photoplethysmography coupled with a deep neural network passively detect atrial fibrillation compared to a criterion-standard ECG?
Smartwatch photoplethysmography using a deep neural network is capable of passively detecting atrial fibrillation, albeit with lower accuracy than standard ECG.
This proof-of-concept study found that smartwatch photoplethysmography coupled with a deep neural network can passively detect AF but with some loss of sensitivity and specificity against a criterion-standard ECG. Further studies will help identify the optimal role for smartwatch-guided rhythm assessment.
Tison et al. (2018) studied this question.