According to a study published in Nature and reported by Science Daily, engineers and physicians collaborated to create a wearable ultrasound device that can monitor both heart anatomy and function. Even after vigorous activity, the stamp-sized gadget may be worn for up to 24 hours with no perceptible loss of capability.
The research is being led by Sheng Xu, a nanoengineering professor at the University of California, San Diego. According to Xu, the initiative’s ultimate purpose is to increase access to ultrasonic technology. An echocardiography (or cardiac ultrasonography) examination nowadays necessitates using experienced specialists and large apparatus.
According to Xu, “everyone can use ultrasonic imaging on the go” using this technology. “The gadget can determine the heart’s blood-pump rate using its artificial intelligence algorithms. The inability of the heart to pump blood is the fundamental cause of many cardiovascular disorders. Thus this is critical. Furthermore, heart problems are usually only apparent once the body is in motion.
Cardiac imaging is crucial for determining long-term heart health, detecting issues early, and treating the seriously ill. Even during strenuous physical activity, this new noninvasive, wearable heart monitor for humans delivers automatic, real-time insights into the heart’s hitherto enigmatic pumping process.
The wearable cardiac monitoring device is built on continuous ultrasound-based imaging of the four chambers and their angles in the heart, with an in-house designed AI engine analyzing a subset of the pictures for clinical significance in real-time. “The rising frequency of cardiovascular illnesses necessitates more advanced and extensive monitoring systems,” Xu added. Continuous and real-time cardiac imaging monitoring can significantly enhance and disrupt the status quo of cardiac diagnosis by giving patients and clinicians more precise data in real-time.
However, existing noninvasive methods have limitations regarding how much data can be captured and collected. Xu’s team created a wearable device capable of capturing pictures of the heart with better spatial resolution, temporal resolution, and contrast. This technology, according to UC San Diego Ph.D. student Hao Huang, “also lowers patient discomfort and overcomes the limits of noninvasive technologies like CT and PET, which might expose patients to radiation.”
As people’s lifestyles change, heart disease is becoming increasingly frequent in younger age groups. The unpredictability of the development and remission of cardiovascular disease symptoms complicates diagnosis. This highlights the need for cutting-edge, all-encompassing, noninvasive, and cost-effective monitoring technology, such as the capabilities of this wearable gadget for long-term cardiac imaging.
The new technology collects data through a skin-like patch worn by the user. The patch measures 1.9 by 2.2 by 0.09 cm, which makes it smaller than a conventional postage stamp. It produces real-time pictures of the heart’s anatomy by transmitting and receiving ultrasonic vibrations. This ultrasonic patch applies easily and stays firmly in place throughout strenuous activity.
The approach gives more therapeutically valuable pictures than were previously accessible by using ultrasound to analyze the left ventricle of the heart from two independent bi-planar viewpoints. To highlight the potential use, the researchers obtained photos of the beating heart during exercise, which is now impossible to achieve with the heavy, immobile equipment commonly seen in hospitals.
Stroke volume, ejection fraction, and cardiac output are all measures of cardiac performance. The amount of blood pumped out by the heart with each heartbeat is referred to as stroke volume; the percentage of blood pumped out of the left ventricle is referred to as ejection fraction; and cardiac output is the total amount of blood pumped out by the heart with each heartbeat is referred to as cardiac output (the volume of blood the heart pumps out every minute).
According to Ruixiang Qi, a master’s student in Xu’s lab at UC San Diego, “specifically, the AI component contains a deep learning model for picture segmentation, an algorithm for heart volume computation, and a data imputation technique.” “Heart volume may be calculated by segmenting the left ventricle and comparing the resulting form and size to the model’s predictions. Image segmentation is the first real-world use of a deep learning model in wearable ultrasonography equipment.
The device can now deliver precise and continuous waveforms of critical cardiac parameters in various physiological situations, such as rest and post-exercise.” As the AI component analyzes the constant stream of images to create numbers and curves, this technology can continually and noninvasively construct curves of these three indices.
