A Wearable Ultrasonic System for Automatic, Continuous, and Noninvasive Monitoring of Central Blood Pressure

用于自动、连续、无创监测中心血压的可穿戴超声波系统

• 批准号: 10504949
• 负责人: Sheng Xu
• 金额: $ 49.21万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10504949
• 关键词: Acoustics; Address; Algorithms; Anterior; Antihypertensive Agents; Arteries; Automatic Data Processing; Awareness; Benchmarking; Blood Pressure; Blood Pressure Monitors; Blood Vessels; Bluetooth; Caliber; Cardiology; Cardiovascular Diseases; Cardiovascular system; Catheterization; Catheters; Cellular Phone; Clinical; Collaborations; Consumption; Custom; Data; Data Set; Dependence; Development; Devices; Diagnosis; Electronics; Elements; Evaluation; Event; Fourier Analysis; Frequencies; Future; General Population; Gold; Grant; Health; Health Care Costs; Hour; Human; Hypertension; Image; Immobilization; Intervention; Location; Machine Learning; Manuals; Maps; Measurement; Measures; Methods; Modeling; Monitor; Noise; Outcome; Participant; Patients; Performance; Peripheral; Phase; Photoplethysmography; Physics; Physiologic pulse; Polymers; Predictive Value; Procedures; Process; Reading; Research; Research Project Grants; Resolution; Risk Assessment; Risk Management; Running; Safety; Series; Shapes; Side; Signal Transduction; Skin; Statistical Data Interpretation; Stretching; Supervision; Surface; Symptoms; System; Techniques; Technology; Time; Training; Transducers; Translating; Ultrasonic Transducer; Ultrasonics; United States National Institutes of Health; Validation; Work; arm; automated algorithm; base; blood pressure control; blood pressure reduction; cardiovascular disorder prevention; cardiovascular risk factor; clinical practice; clinically relevant; computerized data processing; data exchange; deep learning; deep learning algorithm; design; disorder risk; high throughput screening; human error; human subject; hypertension control; hypertension treatment; improved; machine learning algorithm; miniaturize; monitoring device; mortality; multidisciplinary; non-invasive monitor; operation; optical fiber; peripheral blood; prehypertension; printed circuit board; screening; skills; standard of care; tonometry; ultrasound; usability; wearable platform; wireless

PROJECT SUMMARY This proposed project aims to develop a wearable ultrasonic patch for automatic, continuous, and noninvasive central blood pressure monitoring. Hypertension is a “silent killer” since it gradually induces a series of cardiovascular diseases, usually without any obvious symptoms. Compared with brachial blood pressure acquired by the cuff, blood pressure at central locations has been proven to be more valuable for predicting future cardiovascular events and disease risks. Thus, it is essential to measure central blood pressure regularly to maximize the blood pressure management outcome. This research is distinct from all other existing methods for central blood pressure measurements that have a series of different technical challenges, such as the use of invasive procedures, insufficient accuracy, and significant dependence on the operator’s skills. In 2018, the PI’s group invented the first wearable ultrasonic device for central blood pressure recording, supported by an R21 grant from NIH. However, this device still needs cables for power and data transfer, manual processing of the data, and a low signal-to-noise ratio. In this proposed project, we will demonstrate a wearable ultrasonic transducer array integrated with miniaturized wireless control electronics and automatic data processing algorithms. The integrated control electronics will eliminate the bulky setup and connecting wires. The phased-array beamforming will focus and steer the ultrasound beam to search the blood vessels and improve the signal-to-noise ratio and the spatial resolution. All data acquired by the wearable ultrasonic device will be wirelessly transmitted to a terminal receiver (e.g., a smartphone), where a deep learning based algorithm is running for further data processing. The customized algorithm will automatically localize the targeted artery and track both the anterior and posterior walls of the vessel without the supervision of human operators. Thereby, the operator dependence in conventional ultrasound systems will be eliminated, and device usability can be much improved. Finally, the proposed entire system will be validated on patients against arterial catheterization, the current gold standard for central blood pressure monitoring in clinical settings. If successful, this proposed study will provide patients with a device that can access their central blood pressure automatically, continuously, and noninvasively. Using a stretchable platform that matches the softness of the human skin will make a key difference in patient acceptance and monitoring outcomes. The ease of measurements enabled by the automatic algorithm can significantly help high-throughput screening of central blood pressure in the general population and guide the development of antihypertensive drugs, which can eventually translate to a significant reduction in blood pressure associated mortality and healthcare costs.

项目摘要 本计画旨在开发一种可穿戴式超音波贴片， 中央血压监测。高血压是一个“沉默的杀手”，因为它逐渐引起一系列的 心血管疾病，通常没有任何明显的症状。与肱动脉血压相比 通过袖带采集，中心位置的血压已被证明对预测更有价值 未来心血管事件和疾病风险。因此，定期测量中心血压是必要的 最大限度地提高血压管理效果。这项研究不同于所有其他现有的方法 对于具有一系列不同技术挑战的中心血压测量，例如使用 侵入性操作、准确性不足以及对操作者技能的显著依赖。2018年，PI 该小组发明了第一个用于中央血压记录的可穿戴超声设备，由R21支持 来自NIH的资助。然而，该设备仍然需要电缆来进行电力和数据传输，手动处理 数据，以及低信噪比。在这个项目中，我们将展示一个可穿戴的超声波 集成有小型化无线控制电子设备和自动数据处理的换能器阵列 算法集成的控制电子设备将消除笨重的设置和连接线。的 相控阵波束形成将聚焦和引导超声波束以搜索血管并改善血管的收缩。 信噪比和空间分辨率。可穿戴超声波设备获取的所有数据将被 无线发送到终端接收机（例如，智能手机），其中基于深度学习的算法被 进行进一步的数据处理。定制算法将自动定位目标动脉， 跟踪血管的前壁和后壁，而无需人工操作员的监督。因此，在本发明中， 将消除常规超声系统中对操作者的依赖，并且可以 好多了最后，将在患者身上验证拟议的整个系统是否适合动脉插管， 目前临床环境中中央血压监测的金标准。如果成功的话，这个建议 研究将为患者提供一种设备，可以自动，连续， 而且是非侵入性的使用一个与人体皮肤柔软度相匹配的可拉伸平台， 患者接受度和监测结果的差异。测量的便利性， 自动算法可以显着帮助高通量筛选中心血压的一般 人口和指导抗高血压药物的发展，这最终可以转化为一个显着的 降低与血压相关的死亡率和医疗费用。