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New heart monitor could save many lives

The sensor could prevent heart attacks and strokes.

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The wearable cardiac ultrasound imager is flexible, making it ideal for bodies in motion. (Xu Laboratory via SWNS)

By Mark Waghorn via SWNS

A heart monitor has been developed that images the organ as people go about their daily chores.

The postage stamp-sized device can be worn on the chest for up to 24 hours - and works even during strenuous exercises.

It uses ultrasound to assess both structure and function.

Cardiovascular disease is the world's number one killer, claiming around 18 million lives annually.

The sensor could prevent heart attacks and strokes - and identify conditions earlier when drugs and lifestyle changes are most likely to work.

It will make ultrasound more accessible to a larger population.

Project leader Professor Sheng Xu, of the University of California in San Diego, said: "The technology enables anybody to use ultrasound imaging on the go."

(Xu Laboratory, UC San Diego Jacobs School of Engineering via SWNS)

Currently, echocardiograms - ultrasound examinations for the heart - require highly-trained technicians and bulky machines.

An AI (artificial intelligence) algorithm measures how much blood the heart is pumping.

Too little is the cause of most cardiovascular diseases. Issues often manifest only when the body is in motion.

Heart scans assess long-term health, detect problems as they arise and care for critically ill patients.

Hongjie Hu, a postdoctoral researcher in the Xu lab at UC San Diego, and co-first author of the study. (Xu Laboratory via SWNS)

The wearable, non-invasive monitor described in Nature provides real-time, automated insights on the difficult-to-capture pumping activity - even when a person is exercising.

It uses ultrasound to continuously capture images of the four chambers of the heart in different angles and analyze a clinically relevant subset using custom-built AI.

Prof Xu said: "The increasing risk of heart diseases calls for more advanced and inclusive monitoring procedures.

"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 wearable ultrasound sensor is flexible, allowing it to provide a continuous recording of cardiac activities before, during and after exercise.(Xu Laboratory, UC San Diego Jacobs School of Engineering via SWNS)

It provides much better images with higher resolution and contrast than existing non-invasive methods.

Co-author Hao Huang, a Ph.D. student, said: "It also minimizes patient discomfort and overcomes some limitations of noninvasive technologies such as CT and PET, which could expose patients to radiation."

The unique design of the sensor also makes it ideal for bodies in motion.

Co-author Dr. Xiaoxiang Gao said: "The device can be attached to the chest with minimal constraint to the subjects' movement, even providing a continuous recording of cardiac activities before, during and after exercise."

Cardiac diseases are the leading cause of death among the elderly and are also becoming more prevalent among the young due to unhealthy diets and lack of exercise.

The signs of cardiac diseases are transient and unpredictable, making them hard to spot.

This has upped the demand for more advanced, inclusive, non-invasive and cost-effective monitoring technologies such as long-term cardiac imaging.

Co-author Dr. Hongjie Hu said: "The heart undergoes all kinds of different pathologies. 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."

The system gathers information through a wearable patch as soft as human skin, designed for optimal adherence.

It sends and receives ultrasound waves which are used to generate a constant stream of images of the structure of the heart.

Co-author Mohan Li, a master's student, said: "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."

Currently, the patch is connected through cables to a computer, which downloads the data automatically. But the team has already developed a wireless circuit, which will be more appropriate for clinical use.

Prof Xu plans to commercialize the product through Softsonics, a university company spin-off.

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