SleepPPG-Net2: Deep learning generalization for sleep staging from photoplethysmography

arXiv:2404.06869v1 Announce Type: new
Abstract: Background: Sleep staging is a fundamental component in the diagnosis of sleep disorders and the management of sleep health. Traditionally, this analysis is conducted in clinical settings and involves a time-consuming scoring procedure. Recent data-driven algorithms for sleep staging, using the photoplethysmogram (PPG) time series, have shown high performance on local test sets but lower performance on external datasets due to data drift. Methods: This study aimed to develop a generalizable deep learning model for …

abstract algorithms analysis arxiv clinical cs.ai cs.lg data data-driven deep learning diagnosis eess.sp health management scoring series sleep staging time series type