Web proceedings papers

Authors

Barbora Andrášikova , Fedor Lehocki , Milan Tysler , Ana Madevska-Bogdanova , Ivan Kuzmanov , Oto Masar , Marko Spasenovic and Silvia Putekova

Abstract

Blood pressure is a crucial vital sign used as an indicator of patient’s medical state. However, the standard methods of measuring blood pressure continuously are not convenient enough in order to be used versatilely. Critical and life threatening situations such as civil disasters require measuring blood pressure as fast and as accurately as possible without the need of manual calibration. In this paper, we introduce several existing blood pressure estimation techniques using machine learning and deep learning algorithms based on ECG and/or PPG signals acquired from a wearable sensor.

Keywords

cuffless blood pressure · ECG · PPG · machine learning · deep learning