Large Scale Construction in Air Ultrasound Monitoring for Moving Objects, UC San Diego engineers develop integrated systems for deep tissue monitoring.
A team of engineers from the University of California, San Diego has developed the first complete ultrasound system for deep tissue examination, including moving subjects. It enables life-saving cardiac monitoring and marks a major step forward for one of the world’s leading portable ultrasound laboratories.
The article, “A Fully Integrated Portable Ultrasound System for Scanning Deep Tissue and Moving Objects,” appears in the May 22, 2023 issue of Nature Biotechnology.
“This project provides a complete solution for small ultrasound technology, not only that Wearable sensors are being developed, but electronics are also being developed in the form of wearables,” said Muyang Lin, a Ph.D. researcher in the Department of Nanoengineering at UC San Diego and first author of the study. “We have created a truly wearable device that can detect vital signs in deep tissue and air.”
The research comes from the laboratory of Sheng Xu, professor of nano engineering at UC San Diego Jacobs School of Engineering and co-author of the study.
This in detail, a small ultrasound patch system builds on previous laboratory work on the design of soft ultrasonic sensors. However, all older soft ultrasonic sensors require tethers for data and power transmission, which greatly restricts the user’s mobility.
In this work, it includes a small flexible driver circuit that communicates with several ultrasonic transducers to collect and transmit data in the air. Machine learning features help interpret data and track interesting topics.
Based on the findings of the laboratory, the ultrasound patch system enables continuous monitoring of physiological signals from tissues as deep as 164 mm, continuously measuring central blood pressure, heart rate, cardiac output and other physiological indicators up to 12 o’clock at the same time. “This technology has a lot of potential to save and improve lives,” Lin said.
“The sensor can monitor the heart’s activity during exercise. Bad values of blood pressure and heart output, at rest or during exercise, are symptoms of heart failure. For healthy people, our device can measure the heart rate response to exercise in real time and thus provide information about how much training an individual is doing, which can guide the design of training plans.
The patch ultrasound system also represents progress in the development of the Internet of Medical Things (IoMT), a term for a network of medical devices connected to the Internet, transmitting physiological signals to the cloud for computational purposes, research and expertise diagnosis.
Due to the advances in technology and the hard work of doctors in the past few decades, ultrasound has continued to be popular, and Xu Lab is called by First breath as the first and most permanent leader in the field, especially in small things ultrasound.
The lab took fixed and portable devices and made them expandable and portable, revolutionizing the health care system. His strengths lie in part in his collaboration with doctors. “Even though we are engineers, we know the medical problems that doctors face,” Lin said.
“We have a close relationship with our clinical partners and always get valuable feedback from them. This new portable ultrasound technology is a unique approach to many important diagnostic indicators. challenges in clinical practice.
While developing their new invention, the team was surprised to discover that it had more capabilities than originally expected. “At the beginning of this project, we wanted to develop a blood pressure sensor,” Lin said.
“Later, as we made the circuit, developed the algorithm, and gathered clinical information, we thought that this system could measure many other physiological parameters other than blood pressure, such as cardiac output heart rate, muscle stiffness, expiratory sound and others, everything which is important for daily health care or hospital monitoring.
In addition, when the subject is moving, there will be movement between the handheld ultrasonic sensor and the target tissue, requiring constant manual adjustment of the handheld ultrasonic sensor to track the target a lump. In this project, the team developed a machine learning algorithm to analyze the received signals in real time and select the most suitable channel to track the moving target.
However, when an algorithm is trained using data from one subject, this learning may not transfer to other subjects, making the results inconsistent and unreliable.
“We finally made the generality of the machine learning model work by applying an advanced algorithm,” said Ziyang Zhang, a master’s student in the Department of Computer Science and Engineering at UC San Diego and co-first faculty member the author said.
“This algorithm can reduce domain distribution overlap between different subjects, meaning that intelligence can be transferred from one subject to another. We can train an algorithm on one subject and apply it to many other new subjects with less training.
In the future, the sensor will be tested on a larger scale. “So far, we have confirmed the operation of the device on a small and varied scale,” said Xiaoxiang Gao, a postdoctoral researcher in the Department of Nanoengineering at UC San Diego and first author.
“As we think of this device as the next generation of deep tissue monitoring devices, clinical trials are our next step.”
Xu is the co-founder of Softsonics, LLC, which plans to commercialize the technology.
Source: University of California – San Diego
