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.

项目概要 该项目旨在开发一种可穿戴式超声波贴片，用于自动、连续、无创 高血压是一个“无声杀手”，它会逐渐诱发一系列的症状。 心血管疾病与肱动脉血压相比，通常没有任何明显症状。 通过袖带获取的中心位置血压已被证明对于预测更有价值 因此，定期测量中心血压非常重要。 该研究与所有其他现有方法不同。 对于具有一系列不同技术挑战的中心血压测量，例如使用 2018 年，PI 的侵入性操作、准确性不足以及对操作者技能的严重依赖。 小组发明了第一个用于中心血压记录的可穿戴超声波设备，由 R21 支持 然而，该设备仍然需要电缆来进行电源和数据传输、手动处理。 数据和低信噪比在这个拟议的项目中，我们将演示可穿戴超声波。 传感器阵列与小型无线控制电子设备和自动数据处理集成 集成的控制电子设备将消除笨重的设置和连接线。 相控阵波束形成将聚焦并引导超声波束来搜索血管并改善 可穿戴超声设备采集的所有数据都将是信噪比和空间分辨率。 无线传输到终端接收器（例如智能手机），其中基于深度学习的算法 定制的算法将自动定位目标动脉并进行进一步的数据处理。 无需人类操作员的监督即可跟踪容器的前壁和后壁。 传统超声系统对操作员的依赖将被消除，并且设备的可用性可以提高 最后，所提出的整个系统将在患者身上进行动脉导管插入术的验证， 目前临床环境中中央血压监测的黄金标准 如果成功的话，这一提议。 研究将为患者提供一种可以自动连续测量中心血压的设备 使用与人体皮肤柔软度相匹配的可拉伸平台将成为关键。 患者接受度和监测结果的差异。 自动算法可显着帮助一般人群中心血压的高通量筛查 人口并指导抗高血压药物的开发，这最终可以转化为显着的 降低与血压相关的死亡率和医疗费用。