Skin-like, stretchable, and wearable sensors for monitoring QT interval and hemodynamic variables in Atrial Fibrillation

项目摘要 房颤是成人最常见的持续性心律失常，其终生风险为25%-33%。 每年花费美国医疗系统60亿美元。房颤的病症包括充血性心力衰竭， 痴呆症，心输出量减少引起的症状，最重要的是血栓卒中风险增加 因血瘀证。可穿戴技术的最新进展提高了自动对焦的容量和精度 通过在动态环境中监测心率变异性进行诊断。然而，仍然没有 可用的可移动技术，允许持续评估血液动力学影响 房颤和心脏复极的测量也不能确定阿司匹林的心律失常效应 抗心律失常药物。由于房颤的疗效有限，房颤的一些治疗方面仍然存在争议 节律控制干预包括心脏消融和药物治疗，这两种干预措施都有显著的意义 风险。使用III类抗心律失常药物的药物干预特别危险，因为 对可能导致危及生命的室性快速性心律失常的心室复极的影响，例如 尖端扭转力。由于这些问题，如图所示，仔细评估了心室复极 通过心电图上的QT间期，是药物启动过程中需要的。这需要长时间和 在药物加载期间进行昂贵的住院监测，以及在治疗后维持狭窄治疗窗口的困难 出院。有一个可靠的方法来量化血液动力学不稳定的措施，导致一些房颤- 相关症状以及持续监测QT间期和其他临床重要参数 在门诊环境中，将允许临床医生根据个人情况量身定做他们的护理。这项提案旨在完善 灵活、非侵入性的可穿戴系统可持续监控这些关键临床参数，帮助 预测心律并发症和调节药物干预对心律控制和心脏功能的影响 房颤的速率控制。一种传感器套件，由一个小的、无线的和灵活的胸部佩戴的贴片组成，可以测量 基于心电和加速度计的地震心动图(SCG)和无线时间同步柔性肢体 将使用能够监测光体积描记(PPG)信号的装置。目标1将定量地定义 胸部表面QT间期监测的最佳位置。目标2将结合心电、心电地形图和 PPG数据流，并从已知的 与心脏功能和血流动力学有关，使用机器学习获得血流动力学预测 这些复杂关系带来的不稳定性。目标3将解决该可穿戴系统的使用和合规性问题 在违反三类抗心律失常药物负荷和药理学护理标准的临床环境中 心脏复律。这项研究的结果将为房颤症状和 对治疗的反应，向未来的研究和临床护理团队通报主要的生物电学和 生物力学参数是护理不断增长的、老龄化的房颤人口最重要的参数。

Project Summary Atrial Fibrillation (AF) is the most common sustained arrhythmia in adults, carries a lifetime risk of 25-33%, and cost the US healthcare system > 6 Billion dollars a year. Morbidities from AF include congestive heart failure, dementia, symptoms due to decreased cardiac output, and most importantly an elevated thrombotic stroke risk due to blood stasis. Recent advances in wearable technology have increased the capacity and accuracy of AF diagnosis through monitoring heart rate variability in an ambulatory setting. However, there remains no available ambulatory technologies that permit continuous assessment of the hemodynamic effects of AF nor measurements of cardiac repolarization that determine the proarrhythmic effects of antiarrhythmic drugs. Some treatment aspects of AF have remained controversial due to limited efficacy of rhythm control interventions including cardiac ablation and pharmacologic therapy, both of which have significant risks. Pharmacologic interventions using Class III antiarrhythmics are especially risky due to the proarrhythmic effects on ventricular repolarization which can lead to life-threatening ventricular tachyarrhythmias such as torsades de pointes. As a result of these issues, careful assessment of ventricular repolarization, as represented by the QT interval on the electrocardiogram (ECG), is required during drug initiation. This requires lengthy and costly inpatient monitoring during drug loading and difficulties in maintaining the narrow therapeutic window after discharge. Having a reliable method to quantify measures of hemodynamic instability that leads to some AF- related symptoms, as well as continuously monitoring the QT interval and other clinically important parameters in an ambulatory setting would allow clinicians to tailor their care to the individual. This proposal aims to refine a flexible, non-obtrusive wearable system to continuously monitor these key clinical parameters, help in predicting heart rhythm complications and regulate medication intervention for both rhythm control and rate control of AF. A sensor suite consisting of a small, wireless and flexible chest-worn patch that measures both ECG and accelerometer based seismocardiography (SCG) and a wirelessly time synchronized flexible limb unit capable of monitoring photoplethysmographic (PPG) signals will be used. Aim 1 will quantitatively define the optimal location for QT interval monitoring on the surface of the chest. Aim 2 will combine the ECG, SCG, and PPG data streams and extract both unique and time-relational parameters from the signal streams known to be related to cardiac function and hemodynamics, using machine learning to obtain predictions of hemodynamic instability from these complex relationships. Aim 3 will address the use and compliance of this wearable system in a clinical setting against the standard of care during Class III antiarrhythmic drug loading and pharmacologic cardioversion. The results from this study will provide the first ambulatory measures of AF symptoms and responses to treatment, informing future studies and clinical care teams of the dominant bioelectrical and biomechanical parameters that are the most important in the care of the growing, aging population with AF.