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Uncertainty in Blood Pressure Measurement Estimated Using Ensemble-Based Recursive Methodology

Soojeong Lee, Hilmi R. Dajani, Sreeraman Rajan, Gangseong Lee, Voicu Z. Groza

2020Sensors15 citationsDOIOpen Access PDF

Abstract

Automated oscillometric blood pressure monitors are commonly used to measure blood pressure for many patients at home, office, and medical centers, and they have been actively studied recently. These devices usually provide a single blood pressure point and they are not able to indicate the uncertainty of the measured quantity. We propose a new technique using an ensemble-based recursive methodology to measure uncertainty for oscillometric blood pressure measurements. There are three stages we consider: the first stage is pre-learning to initialize good parameters using the bagging technique. In the second stage, we fine-tune the parameters using the ensemble-based recursive methodology that is used to accurately estimate blood pressure and then measure the uncertainty for the systolic blood pressure and diastolic blood pressure in the third stage.

Topics & Concepts

Blood pressureMeasure (data warehouse)Computer scienceData miningMedicineInternal medicineNon-Invasive Vital Sign MonitoringHeart Rate Variability and Autonomic ControlTime Series Analysis and Forecasting