Deep learning ensemble with asymptotic techniques for oscillometric blood pressure estimation.
Journal:
Computer methods and programs in biomedicine
Published Date:
Nov 1, 2017
Abstract
BACKGROUND AND OBJECTIVE: This paper proposes a deep learning based ensemble regression estimator with asymptotic techniques, and offers a method that can decrease uncertainty for oscillometric blood pressure (BP) measurements using the bootstrap and Monte-Carlo approach. While the former is used to estimate SBP and DBP, the latter attempts to determine confidence intervals (CIs) for SBP and DBP based on oscillometric BP measurements.