“This new wearable ultrasound technology is a unique solution to address many vital sign monitoring challenges in clinical practice.”
A group of engineers from the University of California San Diego has achieved a significant milestone by creating the world’s first completely integrated wearable ultrasound system designed for continuous deep-tissue monitoring, even while individuals are on the move.
This groundbreaking development represents a major breakthrough for one of the most prominent wearable ultrasound laboratories globally, offering the potential for life-saving cardiovascular monitoring.
The research paper has been published in today’s edition of Nature Biotechnology.
“We made a truly wearable device that can sense deep tissue vital signs wirelessly,” adds first author Muyang Lin.
The research originates from the laboratory led by Sheng Xu, a professor of nanoengineering at UC San Diego Jacobs School of Engineering and the main author of the study.
This groundbreaking study introduces an innovative autonomous wearable system called the ultrasonic system-on-patch (USoP). It represents a significant advancement over the lab’s previous work in designing soft ultrasonic sensors. Unlike earlier versions that relied on tethering cables for data and power transmission, which significantly limited user mobility, this new system overcomes those constraints. It incorporates a compact and flexible control circuit that wirelessly communicates with an ultrasound transducer array, enabling seamless data collection and transmission. Additionally, a machine learning component assists in interpreting the data and tracking subjects in motion.
According to the lab’s findings, the ultrasonic system-on-patch empowers continuous tracking of physiological signals from deep tissues, reaching depths of up to 164 mm. It has the remarkable capability to continuously measure central blood pressure, heart rate, cardiac output, and various other physiological signals for extended durations of up to twelve hours at a time.
“This technology has lots of potential to save and improve lives,” explains Lin.
“The sensor,” according to the author, “can evaluate cardiovascular function in motion.”
Abnormal blood pressure and cardiac output levels, whether at rest or during exercise, serve as distinguishing characteristics of heart failure.
“For healthy populations, our device can measure cardiovascular responses to exercise in real time and thus provide insights into the actual workout intensity exerted by each person, which can guide the formulation of personalized training plans.”
The USoP signifies a significant advancement in the realm of the Internet of Medical Things (IoMT), which refers to a network of internet-connected medical devices that wirelessly transmit physiological signals to the cloud for computational analysis and professional diagnosis.
Through remarkable technological progress and the dedicated efforts of healthcare professionals, ultrasound has garnered immense attention in recent decades. The Xu lab, renowned as an early and influential pioneer in the field, especially in the domain of wearable ultrasound, is consistently recognized. By transforming stationary and portable devices into stretchable and wearable ones, the lab has revolutionized healthcare monitoring practices, leaving an indelible impact. Its success is attributed, in part, to the lab’s close collaboration with clinicians.
“Although we are engineers, we do know the medical problems that clinicians face,” adds Lin. “We have a close relationship with our clinical collaborators and always get valuable feedback from them. This new wearable ultrasound technology is a unique solution to address many vital sign monitoring challenges in clinical practice.”
During the development of its latest innovation, the team made an unexpected revelation. They were pleasantly surprised to find out that the innovation possessed a broader range of capabilities than originally anticipated.
“At the very beginning of this project, we aimed to build a wireless blood pressure sensor,” explains Lin. “Later on, as we were making the circuit, designing the algorithm and collecting clinical insights, we figured that this system could measure many more critical physiological parameters than blood pressure, such as cardiac output, arterial stiffness, expiratory volume and more, all of which are essential parameters for daily health care or in-hospital monitoring.”
Additionally, when the subject is in motion, there exists a relative motion between the wearable ultrasonic sensor and the targeted tissue. Consequently, frequent manual readjustments of the wearable ultrasonic sensor become necessary to maintain tracking of the moving target. To address this challenge, the research team has successfully devised a machine learning algorithm capable of analyzing received signals and selecting the optimal channel to consistently track the moving target automatically.
Nevertheless, it should be noted that when training the algorithm using data from a single subject, the acquired learning may not be easily transferable to other subjects. This limitation introduces inconsistency and unreliability in the obtained results.
“We eventually made the machine learning model generalization work by applying an advanced adaptation algorithm,” adds co-first author Ziyang Zhang. “This algorithm can automatically minimize the domain distribution discrepancies between different subjects, which means the machine intelligence can be transferred from subject to subject. We can train the algorithm on one subject and apply it to many other new subjects with minimal retraining.”
In the future, extensive testing of the sensor will be conducted on broader populations.
“So far, we have only validated the device performance on a small but diverse population,” points out co-first author Xiaoxiang Gao. “As we envision this device as the next generation of deep-tissue monitoring devices, clinical trials are our next step.”
Source: 10.1038/s41587-023-01800-0
Image Credit: Muyang Lin
