Non-invasive arterial blood pressure measurement and SpO₂ estimation using PPG signal: a deep learning framework.

ABSTRACT:

Background

Monitoring blood pressure and peripheral capillary oxygen saturation plays a crucial role in healthcare management for patients with chronic diseases, especially hypertension and vascular disease. However, current blood pressure measurement methods have intrinsic limitations; for instance, arterial blood pressure is measured by inserting a catheter in the artery causing discomfort and infection.

Method

Photoplethysmogram (PPG) signals can be collected via non-invasive devices, and therefore have stimulated researchers' interest in exploring blood pressure estimation using machine learning and PPG signals as a non-invasive alternative. In this paper, we propose a Transformer-based deep learning architecture that utilizes PPG signals to conduct a personalized estima

SUBMITTER: Chu Y 

PROVIDER: S-EPMC10362790 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature