Camera-based assessment of hemodynamics for non-contact blood pressure estimation

基于摄像头的血流动力学评估，用于非接触式血压估算

• 批准号: 401786308
• 负责人: Professor Dr.-Ing. Sebastian Zaunseder
• 金额: --
• 依托单位: Institut für Informatik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/401786308?language=en
• 关键词: Camera; based; assessment; hemodynamics; non

The project aims at the non-contact blood pressure estimation by using cameras. To that end, we develop generally applicable methods to assess the hemodynamic function from videos and evaluate the proposed methods and their feasibility for blood pressure estimation, respectively, within systematic experiments.Recent works proved (1) that the heart activity multimodally, i.e. by the blood volume pulse and ballistocardiographic effects, affects video recordings and (2) that video recordings allow the spatio-temporal assessment of blood pulsations. We exploit both aspects to derive parameters related to the proximal (via ballistocardiography) and distal (via pulse wave arrival and pulse wave propagation) cardiovascular activity and estimate the beat-to-beat blood pressure from such parameters. Within the project, we firstly develop methods to extract shape-preserved, i.e. morphologically usable, photoplethysmograms (cbPPG) and ballistocardiograms (cbBCG) from videos. The proposed methods make use of spatio-temporal averaging using a non-linear algorithm for signal warping (two-dimensional signal warping). Based on spatially resolved cbPPG, we develop a novel method to estimate the peripheral vascular tone using videos (the so-called perfusion velocity). The perfusion velocity is gained by a probabilistic approach, which determines spatially resolved probability distributions of the peripheral pulse wave velocity and estimates the perfusion velocity from the superposition of local distributions. To eventually estimate the blood pressure, we combine the pulse transit time, which is derived from cbBCG and cbPPG, and the partially complementary perfusion velocity within a multilevel analysis and determine a model for non-contact blood pressure estimation. To validate the proposed methods, we conduct an experimental study comprising 50 healthy subjects undergoing an experimental protocol that was developed for the project. As a result, the project provides methods for the non-contact assessment of hemodynamic characteristics using cameras. Such methods can be applied to estimate the beat-to-beat blood pressure, but even beyond blood pressure estimation, they offer wide opportunities to assess the perfusion and autonomous regulation. Our basic investigations further make a major contribution to characterize the opportunities and limitations of camera-based assessment of vital parameters, particularly related to the spatio-temporal characteristics of pulse wave propagation.

本课题旨在利用摄像头实现非接触式血压测量。为此，我们开发了普遍适用的方法来评估血流动力学功能，从视频和评估所提出的方法和他们的可行性，血压估计，分别在系统的experiments.Recent工作证明（1）心脏活动多模态，即通过血容量脉冲和心冲击描记术的影响，影响视频记录和（2）视频记录允许血液脉动的时空评估。我们利用这两个方面来获得与近端（通过心冲击描记术）和远端（通过脉搏波到达和脉搏波传播）心血管活动相关的参数，并从这些参数中估计心跳到心跳的血压。在该项目中，我们首先开发了从视频中提取形状保持的方法，即形态学上可用的光电容积描记图（cbPPG）和心冲击图（cbBCG）。所提出的方法利用空间-时间平均，使用非线性算法进行信号翘曲（二维信号翘曲）。基于空间分辨的cbPPG，我们开发了一种新的方法来估计外周血管张力使用视频（所谓的灌注速度）。通过概率方法获得灌注速度，该方法确定外周脉搏波速度的空间分辨概率分布，并从局部分布的叠加估计灌注速度。为了最终估计血压，我们联合收割机了脉搏传导时间，这是来自cbBCG和cbPPG，和部分互补灌注速度内的多级分析，并确定一个非接触式血压估计模型。为了验证所提出的方法，我们进行了一项实验研究，包括50名健康受试者进行的实验协议，是为该项目开发的。因此，该项目提供了使用摄像机非接触评估血流动力学特征的方法。这种方法可以应用于估计逐搏血压，但即使在血压估计之外，它们也提供了评估灌注和自主调节的广泛机会。我们的基础研究进一步做出了重大贡献，以表征的机会和限制的相机为基础的评估的重要参数，特别是有关的脉搏波传播的时空特性。