Engineers Develop the First Fully Integrated Wearable Ultrasound System for Deep-Tissue Monitoring

Engineers Develop the First Fully Integrated Wearable Ultrasound System for Deep-Tissue Monitoring

A wearable ultrasonic-system-on-patch for deep tissue monitoring. Credit score: Muyang Lin

A group of engineers from UC San Diego has efficiently created a completely built-in system for deep-tissue monitoring.

A gaggle of engineers from the College of California San Diego have efficiently created the inaugural completely built-in wearable ultrasound system for deep-tissue monitoring, relevant even for cellular people.

This innovation might show essential for monitoring cardiovascular well being and represents a big milestone for one of many foremost labs specializing in wearable ultrasound know-how. Their analysis,was not too long ago printed within the journal Nature Biotechnology.

A Wearable Ultrasonic System on Patch for Cardiac Activity Monitoring

A wearable ultrasonic-system-on-patch for cardiac exercise monitoring. Credit score: Muyang Lin

“This venture provides a whole answer to wearable ultrasound know-how—not solely the wearable sensor, but additionally the management electronics are made in wearable type components,” stated Muyang Lin, a Ph.D. candidate within the Division of Nanoengineering at UC San Diego and the primary writer on the research. “We made a very wearable gadget that may sense deep tissue very important indicators wirelessly.”

The analysis emerges from the lab of Sheng Xu, a professor of nanoengineering at UC San Diego Jacobs College of Engineering and corresponding writer of the research.

This absolutely built-in autonomous wearable ultrasonic system-on-patch (USoP) builds on the lab’s earlier work in smooth ultrasonic sensor design. Nevertheless, earlier smooth ultrasonic sensors all require tethering cables for knowledge and energy transmission, which largely constrains the person’s mobility.

A Wearable Ultrasonic System on Patch for Deep Tissue Monitoring

A wearable ultrasonic-system-on-patch for deep tissue monitoring. Credit score: Muyang Lin

On this work, it features a small, versatile management circuit that communicates with an ultrasound transducer array to gather and transmit knowledge wirelessly. A machine learning component helps interpret the data and track subjects in motion.

According to the lab’s findings, the ultrasonic system-on-patch allows continuous tracking of physiological signals from tissues as deep as 164 mm, continuously measuring central blood pressure, heart rate, cardiac output, and other physiological signals for up to twelve hours at a time.

“This technology has lots of potential to save and improve lives,” Lin said. “The sensor can evaluate cardiovascular function in motion. Abnormal values of blood pressure and cardiac output, at rest or during exercise, are hallmarks 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.”

Wireless Ultrasound Patch

A wearable ultrasonic-system-on-patch mounted on the chest for measuring cardiac activity. Credit: Muyang Lin

The USoP also represents a breakthrough in the development of the Internet of Medical Things (IoMT), a term for a network of medical devices connected to the internet, wirelessly transmitting physiological signals into the cloud for computing, analysis, and professional diagnosis.

Thanks to technological advances and the hard work of clinicians over the last few decades, ultrasound has received an ongoing wave of interest, and the Xu lab is often mentioned in the first breath as an early and enduring leader in the field, particularly in wearable ultrasound.

The lab took devices that were stationary and portable and made them stretchable and wearable, driving a transformation across the landscape of healthcare monitoring. Its strength rests in part on its close collaboration with clinicians.

“Although we are engineers, we do know the medical problems that clinicians face,” Lin said. “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.”

While developing its latest innovation, the team was surprised to discover that it had more capabilities than initially anticipated.

“At the very beginning of this project, we aimed to build a wireless blood pressure sensor,” said 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.”

Moreover, when the subject is in motion, there will be relative movement between the wearable ultrasonic sensor and the tissue target, which will require frequent manual readjustment of the wearable ultrasonic sensor to keep track of the moving target. In this work, the team developed a machine learning algorithm to automatically analyze the received signals and choose the most appropriate channel to keep track of the moving target.

However, when the algorithm is trained using one subject’s data, that learning may not be transferable to other subjects, making the results inconsistent and unreliable.

“We eventually made the machine learning model generalization work by applying an advanced adaptation algorithm,” said Ziyang Zhang, a master’s student in the Department of Computer Science and Engineering at UC San Diego and co-first author on the paper. “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.”

Moving forward, the sensor will be tested among larger populations. “So far, we have only validated the device performance on a small but diverse population,” said Xiaoxiang Gao, a postdoctoral scholar in the Department of NanoEngineering at UC San Diego and co-first author on the study. “As we envision this device as the next generation of deep-tissue monitoring devices, clinical trials are our next step.”

Reference: “A fully integrated wearable ultrasound system to monitor deep tissues in moving subjects” by Muyang Lin, Ziyang Zhang, Xiaoxiang Gao, Yizhou Bian, Ray S. Wu, Geonho Park, Zhiyuan Lou, Zhuorui Zhang, Xiangchen Xu, Xiangjun Chen, Andrea Kang, Xinyi Yang, Wentong Yue, Lu Yin, Chonghe Wang, Baiyan Qi, Sai Zhou, Hongjie Hu, Hao Huang, Mohan Li, Yue Gu, Jing Mu, Albert Yang, Amer Yaghi, Yimu Chen, Yusheng Lei, Chengchangfeng Lu, Ruotao Wang, Joseph Wang, Shu Xiang, Erik B. Kistler, Nuno Vasconcelos and Sheng Xu, 22 May 2023, Nature Biotechnology.
DOI: 10.1038/s41587-023-01800-0

Xu is the co-founder of Softsonics, LLC, which plans to commercialize the technology.

The study was funded by the Air Force Research Laboratory and the National Institutes of Health .

Related posts

The Pioneering Approach to Climate Control


Hollywood actors strike over use of AI in films and other issues


All-Purpose Biosensor Chip With 10,000-Fold Increase in Detection Range


Leave a Comment