Wearable Multi-modality Cuffless Blood Pressure Monitoring

随着人口老龄化，阿尔茨海默病(AD)正成为人们日益沉重的医疗负担 系统。目前的评估和监测方法需要去诊所或医院进行认知 测试和测量大脑、脑脊液和/或脑组织中淀粉样β蛋白(Ab)或tau沉积的标志物 在鲜血中。这些检查繁琐、引人注目、费用昂贵，实际上构成了一种不可改变的护理模式 用于AD的早期检测和监测。理想情况下，大脑健康和AD状态可以在家里进行评估， 类似于家庭心电图仪(ECG)或血压(BP)检查心血管疾病。一个 基于家庭的评估不仅对老年人有局限性，而且对他们来说特别有帮助。 机动性、视力和/或认知状况，也适用于五分之一生活在农村地区的美国老年人和那些 没有足够的机会获得常规医疗护理。然而，要想可行，这样的方法必须足够 成本低，使用方便，无论是大脑监测还是AD评估都还没有实现这一点。 越来越多的证据表明，神经血管功能障碍在发病和/或 阿尔茨海默病的发展，特别是动态神经血管振荡可能参与清除 毒素，如淀粉样β蛋白和tau，通过淋巴系统。我们在马萨诸塞州总医院的团队 开发了一个可穿戴的多模式脑血管监测平台，名为NINcan。这项技术 正在我们的Active R01项目(EB027122)中进行增强和测试，方法是将我们的新表面 在头部水平进行连续、无袖带血压监测的颞动脉血压计(STAT)方法。一个 EB027122的基金补充正在研究将相同的NINScan系统应用于Long-Scan的可行性 持续时间，神经血管和淋巴相关变量的动态监测。 本附录建议调查我们是否可以采用NINcan方法来实现自我或 基于护理者的大脑和AD状态评估，以便最终在家中部署。目标1将涉及 简化NINScan硬件并提供自导说明，以便于在家中收集 老年人和早期阿尔茨海默病患者的神经血管和认知数据。目标2将有较年长的成年人和较早的 AD患者在实验室自行收集多模式大脑和认知数据。我们将进行初步的 测试此类数据是否可用于可靠地识别AD。目标3将寻求将收集到的 神经血管和认知数据集，以及临床特征数据，纳入公共Physionet 作为母公司R01(EB027122)的一部分而开发的数据库。 这一补充有可能提供独特的家庭大脑和认知评估能力， 包括静态和动态血压、神经血管和臀部功能。由此产生的数据将提供关键 洞察自我部署的大脑评估的挑战，以及自我收集的数据对AD的效用 评估，以及提供一种新的能力，在AD以外的许多情况下都很有用。

As the population ages, Alzheimer’s disease (AD) is becoming a growing burden on the health care system. Current assessment and monitoring approaches require visits to the clinic or hospital for cognitive testing and to measure markers of amyloid-beta (Ab) or tau deposits in the brain, in cerebrospinal fluid, and/or in blood. These tests are burdensome, obtrusive, expensive and, in fact, constitute an unstainable care model for early detection and monitoring of AD. Ideally, brain health and AD status could be assessed at home, similar to home-based electrocardiography (ECG) or blood pressure (BP) checks for cardiovascular disease. A home-based assessment would be particularly helpful not only to older adults who have limitations with mobility, vision and/or cognitive status, but also to the 1 in 5 older Americans who live in rural areas, and those with inadequate access to routine medical care. To be viable, however, such an approach must be sufficiently low-cost and easy-to-use, which has not yet been achieved for either brain monitoring or AD assessment. A growing body of evidence suggests that neurovascular dysfunction is important to the onset and/or development of AD, and, in particular, dynamic neurovascular oscillations may be involved in the clearance of toxins such as amyloid beta and tau by the glymphatic system. Our team at Massachusetts General Hospital has developed a wearable, multimodal cerebrovascular monitoring platform, called NINscan. This technology is being enhanced and tested in our active R01 project (EB027122) by incorporating our novel superficial temporal artery tonometry (STAT) method for continuous, cuffless BP monitoring at the level of the head. A funded supplement to EB027122 is investigating the feasibility of adapting this same NINscan system for long- duration, ambulatory monitoring of both neurovascular and glymphatics-relevant variables. This supplement proposes to investigate whether we can adapt the NINscan approach to enable self- or caregiver-based assessment of brain and AD status for eventual deployment at home. Aim 1 will involve simplifying the NINscan hardware and providing self-guided instructions to facilitate at-home collection of neurovascular and cognitive data by older adults and early AD patients. Aim 2 will have older adults and early AD patients self-collect multimodal cerebral and cognitive data in the laboratory. We will conduct a preliminary test of whether such data can be used to reliably identify AD. Aim 3 will seek to incorporate the collected neurovascular and cognitive dataset, along with clinical characterization data, into the public Physionet database being developed as part of the parent R01 (EB027122). This supplement has the potential to provide a unique capability of at-home brain and cognitive assessment, including static and dynamic BP, neurovascular, and glymphatic functioning. The resulting data will provide key insights into the challenges of self-deployed brain assessments, and the utility of self-collected data for AD assessment, as well as providing a novel capability that is useful in numerous conditions beyond AD.