A Smart Ring for Cuffless Blood Pressure to Reduce Health Disparities in People of Color

项目概要/摘要 高血压是最常见的心血管危险因素，对不良后果负有不成比例的责任。 非裔美国人的结果。患有高血压的非裔美国人也更有可能不知道 血压升高，进一步加剧心血管疾病的并发症。因此，检测 非洲裔美国人的准确血压是缓解高血压的关键一步 结果。该项目的目标是创建一款不显眼的无袖血压计 有色人种社区隐匿性高血压的测量和识别。目前的状态 结合袖带的技术很麻烦并且不允许被动/频繁测量。的 无袖套解决方案的趋势主要集中于光电体积描记法 (PPG)，该技术无法操作 适合较深的肤色和体重指数较高的参与者。该项目利用生物阻抗作为 手指佩戴设备形式的传感方式，例如智能戒指。我们的设备提供强大且近乎 连续的生物阻抗读数，对应于血容量和血流动力学变化，这将是 使用机器学习和人工智能算法转化为血压。生物阻抗不具有 PPG 的局限性；它对不同的肤色不敏感，并且具有深层渗透能力，因此 较高的 BMI（以及皮下较厚的脂肪层）不会影响测量结果。主要重点是 我们的调查是为了深入了解隐匿性高血压，目的是获取血压 白天和夜间经常发生。我们提出的技术可以帮助识别某些短期 动态包括血压的变化，并允许有效监测对药物的反应 为乔治亚州亚特兰大的非裔美国人以及德克萨斯州大学城的非裔美国人和拉丁裔社区提供服务。这个 项目有两个目标。目标1旨在验证已开发的智能环技术 德克萨斯 A&M 实验室对具有不同 BMI 的非裔美国人和拉丁裔参与者 (N=60) 进行了研究，没有发现 除了肥胖之外，已知的已有病症，存在各种血压操作（冷升压、 握力和锻炼）和三种姿势（仰卧、站立和坐姿）。目标 2 扩大了验证范围 我们的技术在有或没有高血压病史的非裔美国患者 (N=144) 中进行 佐治亚州亚特兰大的混合实验室和流动环境，以独特的方式探索所报告的现象 的隐匿性高血压，并提高有色人种社区的技术接受度和社会相关性。 经过近十年产学界技术发展提取血压指标 据我们所知，使用 PPG，这项工作首次解决了 PPG 对较暗颜色的有限效果 肤色和 BMI 较高的人。文献表明患病率较高 非裔美国人社区和肥胖人群中的高血压，这进一步要求BMI 独立的技术开发和验证。

PROJECT SUMMARY/ABSTRACT Hypertension is the most prevalent cardiovascular risk factor and disproportionately responsible for adverse outcomes in African Americans. African Americans with hypertension are also more likely to be unaware of elevated blood pressures, which further exacerbates complications of cardiovascular disease. Thus, detection of accurate blood pressure in African Americans is a critical step towards alleviating hypertension disparate outcomes. The objective of this project is to create an unobtrusive cuffless blood pressure monitor for measurement and identification for masked hypertension in communities of color. Current state of the technology that incorporates cuffs is cumbersome and does not allow for passive/frequent measurements. The trends for cuffless solutions are primarily focused on photoplethysmography (PPG) which does not operate well on darker skin tones and on participants with higher BMIs. This project leverages bioimpedance as a sensing modality in the form of a finger-worn device, like smart rings. Our device provides robust and nearly continuous bioimpedance readings, corresponding to blood volume and hemodynamic changes, that will be translated to blood pressure using machine learning and AI algorithms. Bioimpedance does not have the limitations of PPG; it is insensitive to varying skin tones and has deep penetration capabilities and therefore a higher BMI (and a thicker layer of fat under the skin) does not impact the measurements. The principal focus of our investigation is to gain insights into masked hypertension with the objective of capturing blood pressure frequently during the day and at nighttime. Our proposed technology can help identify certain short-term dynamics inclusive of variations of blood pressure and allows effective monitoring of response to medication for African American in Atlanta, GA and African American and Latinx communities in College Station, TX. This project incorporates two aims. Aim 1 intends to validate the smart ring technology that has been developed at Texas A&M on African American and Latinx participants (N=60) with varying BMI in lab settings, with no known pre-existing condition beyond obesity, in presence of various blood pressure maneuvers (cold pressor, handgrip and exercise) and for three postures (supine, standing and sitting). Aim 2 expands the validation of our technology in African American patients (N=144) with and without a history of hypertension in Atlanta, GA in mixed lab and ambulatory settings with a unique focus to explore the reported phenomenon of masked hypertension and to advance technology acceptance and social relevance in communities of color. After nearly ten years of industrial and academic technology development to extract blood pressure indices using PPG, to our knowledge, this effort for the first time addresses the limited effectiveness of PPG on darker skin tones and those who have a higher BMI. The literature demonstrates the higher prevalence of hypertension in African American communities and among those who have obesity, which further calls for BMI independent technology development and validation.