Non-invasive hemodynamic sensor patch for remote, early detection and prevention of heart failure with left bundle branch block

1项目摘要 2. SBIR的长期目标是开发一种远程、非侵入性的心脏早期预警系统， 3心力衰竭风险升高的前驱患者的心力衰竭进展。预警 4系统由患者在家中定期佩戴的无线传感器贴片组成， 5血液动力学和电生理学，以通知心脏病专家心室功能恶化的患者 6、可以从早期干预中获益。目前还没有经过验证的远程监控方法， 7检测心力衰竭。因此，治疗指南限制了大多数侵入性心力衰竭干预 8（例如，植入起搏器或除颤器）的晚期心力衰竭患者，其中一些 9级症状可能不可逆。对于心力衰竭的早期检测的需要是至关重要的，因为心力衰竭 10是65岁以上成人住院的主要原因，也是死亡的主要原因之一。 这项技术将有助于心力衰竭患者的早期发现、预防和治疗， 12他们可以活得更长，更充实的生活。已知特定的血流动力学变化可预测心脏 13例失败结局，但目前用于诊断心脏血流动力学的技术是资源密集型的 14种临床方法，如超声心动图或非特异性远程传感器，如仅测量症状的量表 15心脏衰竭，而不是心脏的潜在功能。该SBIR将产生一种不显眼的血流动力学 16贴片和自动分析算法，以监测特定于心力衰竭病因的信号， 17预测疾病进展。所提出的解决方案以3种具体方式改变了诊断范式： 18个多个血流动力学特定变量的被动测量，直接集成到远程监控中 19个工作流程，易于使用，以支持更有效的慢性病护理服务（例如远程医疗）。 20 Aim 1将评估贴片与临床标准器械（如 21个超声心动图心电图和血压袖带。该目标将验证传感器可以 22以临床级精度可靠地测量血流动力学和电生理信号。它还将调查 23所收集的数据对贴片放置和身体成分变化的敏感性。目标2将调查 24例左束分支传导阻滞患者心力衰竭进展相关的心脏生理改变 25（LBBB），一种与心力衰竭风险增加相关的心脏传导障碍。为了实现这一点， 26名处于不同疾病阶段的LBBB患者将在佩戴无线贴片时睡觉。然后，生理信号 将确定与疾病阶段相关的27个变化。第一阶段的成功完成将验证技术 28能够识别预测心脏的上游生理变化的非侵入式传感器的可行性 29失败这项工作也有更广泛的应用，以改善健康和获得基础知识，通过阐明 30种与LBBB驱动的功能障碍相关的特定进行性血流动力学变化，并通过引入非 31个有创血流动力学远程监测平台，支持未来的纵向心血管研究。

1 Project Abstract 2 The long-term goal of this SBIR is to develop a remote, non-invasive early-warning system for heart 3 failure progression in presymptomatic patients at elevated risk of developing heart failure. The early-warning 4 system consists of a wireless sensor patch worn periodically by patients at home that diagnoses cardiac 5 hemodynamics and electrophysiology to notify cardiologists of patients whose ventricular function is worsening 6 and may benefit from early intervention. Currently there are no validated remote monitoring approaches for early 7 detection of heart failure. Consequently, treatment guidelines restrict most invasive heart failure interventions 8 (e.g. implantation of a pacemaker or defibrillator) to patients suffering from later-stage heart failure where some 9 degree of symptoms may be irreversible. The need for early detection in heart failure is critical, as heart failure 10 is the leading cause of hospitalizations in adults over 65 years old and among the leading causes of mortality. 11 The proposed technology will aid early detection, prevention, and treatment of heart failure patients so 12 they can live longer, more fulfilling lives. Specific hemodynamic changes are known to be predictive of heart 13 failure outcomes, but current technologies used to diagnose cardiac hemodynamics are resource intensive 14 clinical methods like echocardiography or non-specific remote sensors like scales which only measure symptoms 15 of heart failure and not the underlying function of the heart. This SBIR will develop an unobtrusive hemodynamic 16 patch and automated analysis algorithm to monitor signals specific to the etiology of heart failure that are 17 predictive of disease progression. The proposed solution changes the diagnostic paradigm in 3 specific ways: 18 passive measurement of multiple hemodynamic-specific variables, direct integration into remote monitoring 19 workflows, and ease of use to support more efficient chronic care delivery (e.g. telemedicine). 20 Aim 1 will evaluate the accuracy and precision of the patch versus clinical standard devices like 21 echocardiography, electrocardiography, and blood pressure cuffs. This Aim will validate that the sensor can 22 reliably measure hemodynamic and electrophysiological signals at clinical grade accuracy. It will also investigate 23 the sensitivity of the data collected to patch placement and body composition variability. Aim 2 will investigate 24 cardiac physiological changes associated with heart failure progression in patients with left bundle branch block 25 (LBBB), a cardiac conduction disorder associated with increased risk of developing heart failure. To achieve this, 26 LBBB patients at various disease stages will sleep while wearing the wireless patch. Then, physiological signal 27 changes associated with disease stage will be identified. Successful completion of Phase I will validate technical 28 feasibility of a non-invasive sensor capable of identifying upstream physiological changes predictive of heart 29 failure. The work also has broader applications to improve health and gain fundamental knowledge by elucidating 30 specific progressive hemodynamic changes associated with LBBB-driven dysfunction and by introducing a non- 31 invasive hemodynamic remote monitoring platform to empower future longitudinal cardiovascular studies.