Non-invasive measurements of central blood pressures by RF sensors

项目摘要/摘要 动脉血压(BP)和肺动脉压(PAP)是诊断和治疗的基础 体循环和肺动脉高压的管理以及外科和危重病人的监测 病人。系统性高血压是心血管疾病最常见的可改变的危险因素， 世界上死亡和残疾的主要贡献者。肺动脉高压是一组肺性高血压 血管紊乱导致PAP升高、右心衰竭和死亡。它也普遍存在于 重症监护室。肺动脉高压的诊断仍然具有挑战性。 最常见的监测动脉血压的是基于袖带的无创血压计，这种血压计只 输出臂动脉收缩压和舒张压，不同于关键的中央血压，并且容易在 心律失常的存在。不是提供连续的测量，而是将其BP值在多个时间段进行平均 脉搏。有创插管可以直接监测动脉血压，但这项技术并不是没有风险的。 超声心动图、CT扫描和磁学检查对PAP的无创性评估 磁共振成像(MRI)虽然有用，但仍然是可变和依赖于操作者的。因此，右心 插管仍然是诊断PAP和肺动脉高压的金标准，尽管 侵入性的。目前，在家庭或初级保健中监测产后应激障碍是不可行的。 该提案的主要目的是评估非侵入性射频(RF)传感器能否 准确和非侵入性地恢复中央BP和PAP瞬变。我们假设近场 射频载波的相干传感(NCS)，已根据心跳和呼吸进行基准测试 带有黄金标准装置的波形也可以应用于从振动中提取中枢BP 在整个心脏周期中的主动脉和肺动脉的特征。工作原理 类似于探地雷达和充气眼压计，其中希尔伯特-黄变换和 机器学习可用于BP信号处理。 我们的工作将从建立一个幽灵心脏模型开始，该模型将允许直接泵送控制并主办 NCS和基于导管的压力传感器。我们还将探讨多输入多输出(MIMO)网络控制系统 以改进振动特征的局部映射。我们将使用麻醉的猪作为动物模型 主动脉BP和PAP研究，将部署来自体模的类似传感器。数据的精确度 传感器及其跟踪与黄金标准压力导管相关的变化的能力将进行基准测试。 主动脉血压的研究将通过输注肌力调节剂和血管增压剂来修改，而PAP将通过急剧改变 吸入氧气部分(FiO2)，诱导肺表面活性物质耗竭，然后肺复张。另外， 将对动物进行同步的心电图和光体积描记(PPG)检查 能否实现NCS BP读数的非侵入式校准。

Project Summary/Abstract Arterial blood pressure (BP) and pulmonary arterial pressure (PAP) are fundamental for diagnosis and management of both systemic and pulmonary hypertension and for monitoring of surgical and critically ill patients. Systemic hypertension is the most common modifiable risk factor for cardiovascular disease and the leading contributor to mortality and disability in the world. Pulmonary hypertension is a group of pulmonary vascular disorders leading to increased PAP, right ventricular failure, and death. It is also common in the intensive care unit. Diagnosis of pulmonary hypertension remains challenging. Arterial BP is most commonly monitored with the non-invasive cuff-based sphygmomanometer, which only outputs brachial systolic and diastolic BP, differs from the critical central BP, and is prone to errors in the presence of arrhythmias. Instead of providing a continuous measurement, its BP values are averaged over many pulses. Invasive catheterization allows for direct arterial BP monitoring, but the technique is not risk-free. Noninvasive estimates of PAP from echocardiography, computed tomography (CT) scan and magnetic resonance imaging (MRI), although useful, remain variable and operator-dependent. Therefore, right heart catheterization is still the gold-standard diagnosis for PAP and pulmonary hypertension, despite being highly invasive. Monitoring of PAP at home or primary care is currently unfeasible. The overarching aim of this proposal is to evaluate whether a non-invasive radio-frequency (RF) sensor can retrieve central BP and PAP transients accurately and non-invasively. We hypothesize that the near-field coherent sensing (NCS) by RF carriers, which has been benchmarked on heartbeat and respiration waveforms with the gold-standard devices, can also be applied to derive central BP from the vibration characteristics of the aorta and pulmonary arteries in the entire cardiac cycle. The principle of operation is similar to that of the ground penetrating radar and air-puff tonometry, where Hilbert-Huang Transforms and machine learning can be adapted for BP signal processing. Our effort will start from building a phantom heart model, which will allow direct pumping control and host the NCS and catheter-based pressure sensors. We will also explore the multiple-input-multiple-output (MIMO) NCS to improve the local mapping of vibration characteristics. We will use anesthetized pigs as animal models for aortic BP and PAP studies, where similar sensors from the phantom will be deployed. The accuracy of the sensors and their ability to track changes in relation to the gold-standard pressure catheters will be benchmarked. Aortic BP studies will be modified by infusion of inotropes and vasopressors, while PAP by acutely changing the fraction of inspired oxygen (FiO2) and by inducing surfactant depletion followed by lung recruitment. Additionally, electrocardiogram (ECG) and photo-plethysmography (PPG) will be synchronized on the animals to investigate whether noninvasive calibration of the NCS BP readout can be realized.