Arterial Blood Pressure

Arterial blood pressure (ABP) research focuses on accurate and continuous non-invasive measurement, crucial for cardiovascular health monitoring and disease management. Current efforts concentrate on developing advanced machine learning models, including transformer networks and invertible neural networks, to reconstruct ABP waveforms from readily available signals like photoplethysmography (PPG) and even facial video analysis. These methods aim to improve accuracy and reduce reliance on traditional, less convenient cuff-based measurements. Successful development of these technologies would significantly impact both clinical practice and preventative healthcare by enabling continuous, accessible ABP monitoring.