Department of Computer Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea.
School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N6N5, Canada.
Sensors (Basel). 2020 Apr 8;20(7):2108. doi: 10.3390/s20072108.
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.
自动示波法血压计常用于家庭、办公室和医疗中心测量许多患者的血压,最近它们得到了积极的研究。这些设备通常提供一个单一的血压点,并且不能指示测量量的不确定性。我们提出了一种使用基于集成的递归方法来测量示波法血压测量不确定性的新技术。我们考虑了三个阶段:第一阶段是预学习,使用袋装技术初始化良好的参数。在第二阶段,我们使用基于集成的递归方法来微调参数,该方法用于准确估计血压,然后在第三阶段测量收缩压和舒张压的不确定性。