Researchers Develop Wearable Sensor for Remote Cardiac Imaging
A recent study described the creation of a wearable ultrasound sensor that can review patient heart function and structure remotely.
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By - Published in Nature, recent research led by the University of California San Diego described how patients could engage in remote cardiac imaging through a wearable ultrasound sensor that measures the amount of blood pumped by the heart.
When evaluating long-term heart health, cardiac imagining is a vital tool in detecting issues and determining care plans. Among the elderly, cardiac diseases are a leading cause of death, and signs can be hard to foresee, the press release noted. This issue leads to an increased demand for innovative and cost-effective monitoring devices.
With the goal of expanding the population that has access to ultrasounds, researchers from the University of California San Diego are leading a project that uses custom artificial intelligence (AI) algorithms to create a device that can perform cardiac imaging remotely.
“The increasing risk of heart diseases calls for more advanced and inclusive monitoring procedures,” Sheng Xu, PhD, a professor of nanoengineering at the University of California San Diego, who is heading the project, in a press release. “By providing patients and doctors with more thorough details, continuous and real-time cardiac image monitoring is poised to fundamentally optimize and reshape the paradigm of cardiac diagnoses.”
The device consists of a small patch worn on the skin that can use ultrasounds to capture images of the four heart chambers. It then uses custom-built AI technology to analyze a subset of the images.
As the heart is monitored, its performance is characterized by three factors: stroke volume, ejection fraction, and cardiac output. Stroke volume is the amount of blood pumped by the heart each beat, ejection fraction is the percentage pumped out of the left ventricle each beat, and cardiac output is the volume of blood pumped out each minute.
“A deep learning model automatically segments the shape of the left ventricle from the continuous image recording, extracting its volume frame-by-frame and yielding waveforms to measure stroke volume, cardiac output, and ejection fraction,” said Mohan Li, a master’s student in the Xu group at UC San Diego, in a press release.
Currently, the patch is connected to a computer through cables, which can download the data, but the research team has developed a wireless circuit for the patch.
Further, Xu recommends next steps include B-mode imaging to allow for more diagnostic capabilities that include different organs, designing a soft imager to allow for the coverage of more positions, the miniaturization of the back-end system that is used to power the soft imager, and developing a machine-learning model that can include more subjects.
Xu plans to commercialize the technology through Softsonics, a UC San Diego spinoff he co-founded.
This is the latest effort to develop and integrate technology to enable remote care.
Robert Wood Johnson University Hospital doctors tested a tele-cardiac ultrasound system in February 2022. The system leveraged videoconferencing technology to perform remote diagnostic ultrasounds.
Researchers noted that the technology could increase patient access to diagnostic ultrasound imaging, along with other benefits such as reductions in travel times and costs and earlier disease detection. Along with this, the system could also benefit healthcare professionals by addressing the existing shortage of ultrasound technologists and sonographers.
