Tiny Patch for Cardiac Ultrasound Imaging


Engineers at the University of California San Diego have developed a wearable ultrasound system for cardiac imaging. The postage stamp-sized patch can be worn on the skin of the chest and uses AI and ultrasound waves to perform advanced imaging of the heart. The technology can even be worn to perform cardiac ultrasound imaging during exercise. Each patch can be worn for up to 24 hours, and provides information on how much blood the heart is pumping, a key metric in detecting and appraising a variety of cardiac issues. The researchers hope that the technology may lead to more accessible and widespread cardiac monitoring.

Cardiac imaging is a key technique in assessing heart health. However, it typically is not possible during vigorous activity, such as daily exercise, despite the fact that imaging during such times may reveal a lot about the heart. “The heart undergoes all kinds of different pathologies,” said Hongjie Hu, a researcher involved in the study. “Cardiac imaging will disclose the true story underneath. Whether it be that a strong but normal contraction of heart chambers leads to the fluctuation of volumes, or that a cardiac morphological problem has occurred as an emergency, real-time image monitoring on the heart tells the whole picture in vivid detail and visual effect.”   

To address this, these researchers have developed a postage stamp-sized ultrasound patch that can perform advanced imaging on the go. The device can provide images of the heart in real time, and uses AI to interpret the reflected acoustic waves and calculate a variety of hemodynamic parameters, including stroke volume, ejection fraction, and cardiac output.

“Specifically, the AI component involves a deep learning model for image segmentation, an algorithm for heart volume calculation, and a data imputation algorithm,” said Ruixiang Qi, another researcher involved in the study. “We use this machine learning model to calculate the heart volume based on the shape and area of the left ventricle segmentation. The imaging-segmentation deep learning model is the first to be functionalized in wearable ultrasound devices. It enables the device to provide accurate and continuous waveforms of key cardiac indices in different physical states, including static and after exercise, which has never been achieved before.”

At present, the prototype devices still require a wired tether to transmit their data, but the researchers are working on a wireless version for an upcoming publication. The researchers also have plans to commercialize the technology.

Study in journal Nature: A wearable cardiac ultrasound imager


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