基于图像的脉搏传递时间非接触式血压评估

Po-Wei Huang, Chun-Hao Lin, Meng-Liang Chung, Tzu-Min Lin, Bing-Fei Wu
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引用次数: 15

摘要

近年来,人们越来越关注血压监测。在各种测量方法中,基于脉冲传输时间(PTT)的监测仪以其连续、无断口的特点受到了广泛的关注。此外,一些研究提出了一种奇特的方法来估计光容积脉搏波(PPG)信号,只需通过常规的网络摄像头。然而,关于这两种先进技术的整合问题的文献出现得缓慢而分散。此外,由于数据的缺乏,基于PTT的BP预测模型的精度往往受到限制。为了解决上述问题,我们提出了一种基于图像的BP测量算法,该算法将MIMICII数据库的学习结果迁移到实际任务中。该研究还引入了新定义的PTT特征,这些特征特别适用于基于图像的PPG和域自适应。与现有算法相比,SBP评价的均方根误差从15.08降低到14.02。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image based contactless blood pressure assessment using Pulse Transit Time
Recent years have seen increased attention being given to Blood Pressure (BP) monitoring. Among all kinds of measurements, the monitors based on Pulse Transit Time (PTT) have gain plenty of attention due to its continuous and cuffless features. Additionally, several studies proposed a fancy way to estimate photoplethysmography (PPG) signal simply via a regular webcam. Nevertheless, literatures on issues of integrating these two advanced techniques have emerged on a slowly and scattered way. Furthermore, accuracy of BP prediction model based on PTT is often limited due to the lack of data. To address the above-mentioned problems, we proposed an image based BP measurement algorithm using k-nearest neighbor and transfer learning results from MIMICII database to real task. The study also introduces newly defined PTT features which are especially suitable for image based PPG and domain adaptation. Compared with the state-of-the-art algorithm, root mean square error of SBP evaluation has been reduced from 15.08 to 14.02.
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