TL;DR:
- Engineers at UC San Diego have developed the first fully integrated wearable ultrasound system for deep-tissue monitoring.
- The system enables cardiovascular monitoring and is a major breakthrough for wearable ultrasound technology.
- It includes a wearable sensor and control electronics in wearable form factors.
- The system can wirelessly sense deep tissue vital signs.
- The technology allows continuous tracking of physiological signals up to 164 mm deep.
- It can measure central blood pressure, heart rate, cardiac output, and other physiological signals for up to twelve hours.
- The device has potential applications in evaluating cardiovascular function during exercise and personalized training plans.
- It contributes to the development of the Internet of Medical Things (IoMT).
- The Xu lab at UC San Diego is a leader in wearable ultrasound technology.
- Collaboration with clinicians helps address vital sign monitoring challenges.
- The system has capabilities beyond the initial goal, measuring additional physiological parameters.
- A machine learning algorithm assists in tracking moving targets.
- An advanced adaptation algorithm improves the algorithm’s generalization across different subjects.
- The sensor will undergo testing in larger populations and clinical trials.
- Softsonics, LLC, plans to commercialize the technology.
Main AI News:
A team of engineers at the University of California San Diego has achieved a significant milestone in the field of wearable ultrasound technology. They have successfully developed the world’s first fully integrated wearable ultrasound system that enables deep-tissue monitoring, even for individuals on the move. This groundbreaking advancement has the potential to revolutionize cardiovascular monitoring, offering life-saving benefits. The remarkable achievement has positioned the UC San Diego wearable ultrasound lab at the forefront of innovation in this domain. The research paper titled “A fully integrated wearable ultrasound system to monitor deep tissues in moving subjects” has been published in the prestigious May 22, 2023 issue of Nature Biotechnology.
Muyang Lin, a Ph.D. candidate from the Department of Nanoengineering at UC San Diego and the first author of the study, explained, “This project provides a comprehensive solution to wearable ultrasound technology. We have not only developed a wearable sensor, but we have also successfully integrated control electronics into wearable form factors. Our achievement lies in creating a truly wearable device that wirelessly senses vital signs from deep tissues.”
The research work emerged from the laboratory of Professor Sheng Xu, an esteemed figure in the field of nanoengineering at UC San Diego Jacobs School of Engineering and the corresponding author of the study.
This fully integrated autonomous wearable ultrasonic system-on-patch (USoP) builds upon the lab’s previous work in designing soft ultrasonic sensors. However, unlike previous iterations, which required tethering cables for data and power transmission, this new system features a compact and flexible control circuit. This circuit communicates wirelessly with an ultrasound transducer array, enabling seamless data collection and transmission. Additionally, a machine learning component has been incorporated to interpret the data and track subjects in motion.
According to the lab’s findings, the ultrasonic system-on-patch, known as USoP, allows continuous tracking of physiological signals from deep tissues, reaching depths of up to 164 mm. This cutting-edge technology enables the continuous measurement of central blood pressure, heart rate, cardiac output, and other essential physiological signals for an extended period of up to twelve hours.
Lin emphasized the transformative potential of this technology, stating, “This technology holds immense potential to save and improve lives. Our sensor can assess cardiovascular function even when individuals are in motion. Abnormal values of blood pressure and cardiac output, whether at rest or during exercise, are indicative of heart failure. For the general population, our device can measure cardiovascular responses to exercise in real time, providing valuable insights into each person’s actual workout intensity. This data can then be used to develop personalized training plans.”
The USoP also represents a major breakthrough in the development of the Internet of Medical Things (IoMT), a network of medical devices interconnected through the Internet. The USoP wirelessly transmits physiological signals to the cloud, where they can be processed, analyzed, and used for a professional diagnosis. This advancement highlights the potential of wearable ultrasound technology to contribute to the future of healthcare.
The Xu lab’s contributions to the field of ultrasound have gained widespread recognition thanks to their transformative efforts in turning stationary and portable devices into stretchable and wearable ones. This shift has led to a paradigm shift in healthcare monitoring. The lab’s success can be attributed, in part, to its close collaboration with clinicians. Lin acknowledged this collaborative approach, stating, “Although we are engineers, we understand the medical challenges faced by clinicians. We maintain a close relationship with our clinical collaborators and greatly value their feedback. Our new wearable ultrasound technology provides a unique solution to numerous vital sign monitoring challenges encountered in clinical practice.”
During the development of their latest innovation, the team discovered that the system possessed even more capabilities than originally envisioned. Lin explained, “Initially, our goal for this project was to build a wireless blood pressure sensor. However, as we progressed with the circuit design, algorithm development, and data collection, we realized that our system could measure many more critical physiological parameters beyond blood pressure. These parameters include cardiac output, arterial stiffness, expiratory volume, and more. All of these measurements are essential for daily healthcare and in-hospital monitoring.”
One of the challenges faced by wearable ultrasonic sensors is the relative movement between the sensor and the tissue target when the subject is in motion. This movement necessitates frequent manual readjustment of the sensor to maintain tracking of the moving target. In response, the team developed a machine learning algorithm that automatically analyzes the received signals and selects the most appropriate channel for tracking the moving target.
However, a limitation arose when attempting to train the algorithm using data from a single subject. The algorithm’s learning did not generalize well to other subjects, resulting in inconsistent and unreliable results. To overcome this challenge, Ziyang Zhang, a master’s student in the Department of Computer Science and Engineering at UC San Diego and co-first author of the paper, explained, “We managed to address the issue of generalization by applying an advanced adaptation algorithm. This algorithm minimizes the discrepancies in domain distribution between different subjects, allowing the machine intelligence to be transferred from one subject to another. We can train the algorithm on a single subject and then apply it to numerous new subjects with minimal retraining.”
Moving forward, the wearable ultrasound sensor will undergo testing on larger populations. Xiaoxiang Gao, a postdoctoral scholar in the Department of Nanoengineering at UC San Diego and co-first author of the study, stated, “Currently, we have validated the device’s performance on a small but diverse population. As we envision this device as the next generation of deep-tissue monitoring devices, our next step involves conducting clinical trials.”
Professor Sheng Xu, in addition to his academic role, is the co-founder of Softsonics, LLC. The company plans to commercialize this groundbreaking technology, ensuring its accessibility to the wider population and contributing to the advancement of healthcare worldwide.
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