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NIHNATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERINGR01

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

Completed
Institution
UNIVERSITY OF CALIFORNIA, SAN DIEGO, CA
Principal investigator
Sheng Xu
Funding
$536K
Duration
2022–2026
Open portfolio

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Abstract

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.

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R01NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERINGImaging Technology Development Study Section[ITD]wearablepressureautomaticbloodblood pressureultrasonicsignal-to-noise ratiopressure monitoring

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