A Scoping Review of Deep Learning Methods for Photoplethysmography Data

Photoplethysmography (PPG) is a non-invasive optical sensing technique widely used to capture hemodynamic information, with broad deployment in both clinical monitoring systems and wearable devices. In recent years, the integration of deep learning has substantially advanced PPG signal analysis and expanded its applications across healthcare and non-healthcare domains.

We conducted a comprehensive literature search for studies applying deep learning to PPG data published between January 1, 2017 and December 31, 2025, using Google Scholar, PubMed, and Dimensions. The included studies were analyzed from three key perspectives: tasks, models, and data.