Continuous monitoring of vascular age by pulse wave velocity using wearable ECG and PPG sensors

背景虽然健康老龄化是我们这个时代最重要的挑战之一，但在正常生活中监测衰老是困难的。长期的血管老化是日常生活中发生的许多破坏性事件的结果，目前这些事件没有被发现。使用低成本设备连续测量老龄化的能力将为测试旨在减缓大量个人老龄化的干预措施提供机会。血管渐进性僵硬是人类衰老最重要的特征之一。重要的是，动脉硬度可以无创地测量为脉搏波速度(PWV)，被视为最重要的血管年龄生物标志物，但目前需要昂贵而笨重的设备和训练有素的研究人员来测量。然而，像健身手镯和智能手表这样的个人设备现在能够测量各种生物信息，包括心脏的血流和电活动。这些信息可以用来实时计算每一次心跳的PWV，并提供关于血管生物学年龄的即时信息。更重要的是，这一方法将允许确定加速和减缓个人衰老的因素，并监测个人抗衰老疗法的成功。到目前为止，还没有任何技术可以完成这项任务。目的建议的研究在当前的项目中，我们希望开发出低成本的方法，以便在现实生活中使用可穿戴设备来监测个人的“血管年龄”，或者设计一个具有可用部件的原型设备。在该项目的第一阶段，我们将建立一个开发工具包，以集成来自心电(心电图，心脏电活动)和PPG(光体积描记，皮肤血液流动)传感器的数据，计算PWV，并创建集成数据的有用可视化。然后，我们将测试不同年龄和血管疾病患者在不同条件下测量PWV的准确性、有效性和性能，并将结果与测量PWV的金标准方法(眼压计)进行比较。此外，我们将设计一个由低成本标准传感器组件(由Surrey Sensors Ltd.)构建的原型设备。并评估现有的低成本设备是否可以用于随着时间的推移持续监测PWV，以帮助我们决定下一步的重点。FUTURE DIRECTIONS实现这些目标将为明年进行第二次应用奠定基础。在第二步中，我们将建造少量原型设备和/或开发软件解决方案，以便使用现有健身设备的传感器数据进行持续的PWV测量。然后，我们将在不同年龄段的人中测试连续PWV在现实生活中的实用性和适用性，以建立正常值。此外，我们希望通过将测量结果与医院常规导管操作中侵入性测量的PWV进行比较来验证测量结果。在第三步中，我们计划进行一项概念验证研究，以证明连续PWV测量的能力，以检测动脉僵硬对生活方式干预的急性反应，如健康饮食和动脉硬化随时间的慢性变化(血管老化轨迹)。在未来的阶段，我们希望能够在更大的人群中测试连续的PWV测量，可能是与工业界、NHS合作，并使用人们已经拥有的设备的传感器数据。然后，可以通过机器学习将大数据集与其他与健康相关的个人数据一起分析，以确定老化模式和医疗干预对血管老化轨迹的影响。

BACKGROUNDWhile healthy ageing is one of the most important challenges of our time, it is difficult to monitor ageing during normal life. Longterm vascular ageing is the results of many injurious events that occur during everyday life and currently go undetected. The ability to continuously measure ageing with low cost devices would open opportunities to test interventions that aim to slow ageing in a large number of individual people. Progressive stiffening of the blood vessels is one of the most important features of human ageing. Importantly, arterial stiffness can be measured non-invasively as pulse wave velocity (PWV) and is viewed as the most important biomarker of vascular age, but it currently requires costly and bulky equipment and trained researchers to measure. However, personal devices like fitness bracelets and smart watches are now able to measure a variety of biological information including blood flow and electrical activity of the heart. This information could be used to calculate PWV with each heartbeat in real time and provide immediate information on the biological age of the blood vessels. More importantly, this approach would allow the identification of factors that accelerate and slow ageing in an individual person and monitor the success of 'anti-ageing' therapies in an individual person. So far, no technology is available that fulfils this task.OBJECTIVES OF PROPOSED RESEARCHIn the current project, we wish to develop low-cost methods to allow monitoring of individual 'vascular age' at scale during real life using wearables or design a prototype device with available components. In this first phase of the project, we will set up a developmental tool kit to integrate data from ECG (electrocardiogram, electrical activity of the heart) and PPG (photoplethysmography, blood flow in the skin) sensors, calculate PWV, and create useful visualization of integrated data. We will then test the accuracy, validity, and performance of PWV measurements in people at different age and with vascular disease under different conditions and compare the results with gold standard methods (tonometry) to measure PWV. Furthermore, we will design a prototype device build from low-cost standard sensor components (by Surrey Sensors Ltd.) and evaluate if existing low-cost devices can be used for continuous monitoring of PWV over time to help us decide on the focus of the next steps.FUTURE DIRECTIONReaching these objectives will form the basis of moving forward with a second application next year. In this second step, we will build a small number of prototype devices to and/or develop a software solution for using sensor data from existing fitness devices for continuous PWV measurements. We will then test the utility and applicability of continuous PWV in real life in people of different ages to establish normal values. Furthermore, we hope to validate the measurements by comparing results with invasively measured PWV during routine catheter procedures in the hospital. In a third step, we plan to perform a proof-of-concept study to demonstrate the abilities of continuous PWV measurements to detect acute responses of arterial stiffness to life-style interventions such as healthy diet and chronic changes in arterial stiffening over time (vascular ageing trajectory). In a future stage, we hope to be able to test the continuous PWV measurements in larger groups of people, potentially in collaboration with industry, NHS, and using sensor data from devices that people already own. Large data sets can then be analysed together with other individual health related data by machine learning to identify ageing patterns and effect of healthcare interventions on trajectories of vascular ageing.