Key result
An ensemble-based recursive methodology was proposed to accurately estimate blood pressure and measure the uncertainty for systolic and diastolic blood pressure measurements.
Why the study?
Automated oscillometric blood pressure monitors usually provide a single measurement point and cannot indicate the uncertainty of the measured quantity.
The proposed ensemble-based recursive methodology provides a novel computational approach to estimate the uncertainty of automated oscillometric blood pressure measurements.
May advance sensor-based BP monitoring; leaves open prospective validation before clinical use.
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.
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Lee et al. (2020) studied Blood pressure measurement. Ensemble-based recursive methodology was evaluated on Uncertainty for systolic and diastolic blood pressure. An ensemble-based recursive methodology was proposed to accurately estimate blood pressure and measure the uncertainty for systolic and diastolic blood pressure measurements.
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