Cuffless models to infer blood pressure from bioimpedance

无袖带模型可根据生物阻抗推断血压

• 批准号: 2319920
• 负责人: Benjamin Sanchez Terrones
• 金额: $ 45万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2319920&HistoricalAwards=false
• 关键词: Cuffless; models; infer; blood; pressure

Measurement of blood pressure (BP) is essential for early diagnosis and management of hypertension, a condition that 45% of US adults have and a risk factor for development of heart failure, the leading cause of death in the US. Worldwide, hypertension is one of the largest public health epidemics. Compared to ambulatory BP measurements, frequent out-of-clinic BP measurements are better predictors of cardiovascular events but, today, existing clinically-accurate technologies to measure BP require costly, uncomfortable, and cumbersome devices that prevent their extended use outside of the clinic. Given substantial healthcare and mortality burden of heart failure, rising healthcare costs, and the aging population, continued technological improvements to aid heart failure prevention, management, and surveillance are extremely important. The goal of this project is to address this need for an accurate, inexpensive, easy-to use device for continuously monitoring BP through the development of a novel wearable watch built for this purpose. This new technology will be a game-changer to protect at-risk individuals and effectively manage patients with hypertension proactively across the care continuum and reduce hospitalizations associated with hypertension. This study will also serve as fertile ground to support students in continuing their careers at the intersection of STEM and human oriented research.One tool that is well-suited for unobtrusive BP monitoring is bioimpedance (BioZ). In BioZ, an imperceptible electrical current is passed through the body to obtain insights into how blood flows through arteries and veins. Here, the Investigators propose to develop new measurement methods rooted with fluid and electricity principles to create a new BioZ sensing technology capable of enabling continuous, cuffless, and convenient BP monitoring. For this, a novel aspect of the approach taken will be the application of BioZ in conjunction with physiological, computational, and machine learning models to establish the underlying biological sources at the cellular level relating both signals. Once the models have been established and optimized to link BP to BioZ, the prediction accuracy will be evaluated in a cohort of individuals representative of a wide range of body indices and age groups.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

测量血压（BP）对于高血压的早期诊断和管理至关重要，高血压是45%的美国成年人患有的疾病，也是心力衰竭发展的风险因素，心力衰竭是美国的主要死亡原因。在世界范围内，高血压是最大的公共卫生流行病之一。与动态BP测量相比，频繁的门诊外BP测量是心血管事件的更好预测因子，但是，今天，现有的临床精确测量BP的技术需要昂贵、不舒适和笨重的设备，这阻止了它们在门诊外的扩展使用。鉴于心力衰竭的巨大医疗保健和死亡率负担、不断上升的医疗保健成本和人口老龄化，持续的技术改进以帮助心力衰竭预防、管理和监测是极其重要的。 该项目的目标是通过开发一种用于此目的的新型可穿戴手表来满足对准确，廉价，易于使用的设备的需求，以持续监测BP。 这项新技术将改变游戏规则，以保护高危人群，并在整个护理过程中主动有效地管理高血压患者，减少与高血压相关的住院治疗。这项研究也将作为肥沃的土壤，以支持学生在STEM和以人为本的研究的交叉点继续他们的职业生涯。一个非常适合非侵入性BP监测的工具是生物阻抗（BioZ）。在BioZ中，一种难以察觉的电流通过身体，以了解血液如何流过动脉和静脉。在这里，研究人员建议开发基于流体和电原理的新测量方法，以创建一种新的BioZ传感技术，能够实现连续、无袖带和方便的BP监测。为此，所采取的方法的一个新方面将是BioZ与生理，计算和机器学习模型相结合的应用，以在细胞水平上建立与两种信号相关的潜在生物来源。 一旦建立并优化模型，将BP与BioZ联系起来，预测准确性将在一组代表广泛身体指数和年龄组的个人中进行评估。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。