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.

Additional Metadata
Keywords confidence interval, deep neural network, ensemble method, oscillometry blood pressure measurement, uncertainty
Persistent URL dx.doi.org/10.3390/s20072108
Journal Sensors (Basel, Switzerland)
Citation
Lee, S. (Soojeong), Dajani, H.R. (Hilmi R.), Rajan, S, Lee, G. (Gangseong), & Groza, V.Z. (Voicu Z.). (2020). Uncertainty in Blood Pressure Measurement Estimated Using Ensemble-Based Recursive Methodology. Sensors (Basel, Switzerland), 20(7). doi:10.3390/s20072108