KAIST: Early Diagnosis of Cardiovascular Diseases with Wireless Electronic Patch for Blood Flow Measurement

A technology enabling more precise real-time measurement of blood flow using a wireless electronic patch attached to the skin has been developed. This innovation reduces the inconvenience of having to visit a hospital and rely on specialized equipment for accurate blood flow measurement, and is expected to contribute to the early diagnosis of cardiovascular diseases.

AI-generated image. KAIST

On March 5, KAIST announced that the research team led by Professor Kyungha Kwon in the School of Electrical Engineering has developed a wireless wearable blood flow measurement system by combining deep learning with multi-layer thermal sensing technology.

This device uses a non-invasive method to simultaneously measure both blood flow velocity and vessel depth without directly contacting the blood vessel. Vessel depth is a key variable needed to calculate blood flow accurately, as the sensor signal changes depending on how deep the vessel is located beneath the skin.

Until now, ultrasound and optical methods have mainly been used to determine vessel depth. However, these devices are typically large and their accuracy decreases as vessel depth increases.

To address this, the research team focused on the fact that "when blood flows, it causes micro thermal movements in the surrounding area." They developed a "multi-layer thermal sensing" technology, which allows for three-dimensional analysis of heat transfer paths by placing temperature sensors at different depths.

In addition, they applied a deep learning algorithm to successfully separate and extract, in real time, both the vessel depth and the actual blood flow velocity from the complex body temperature distribution. Applying artificial intelligence (AI) to distinguish the vessel depth and true blood flow velocity within complicated temperature distributions is also a key achievement of this study.

(From left) Yongmin Sim and Yosep Park, students at KAIST, and Professor Kyeongha Kwon. KAIST

Experimental results showed that the wireless electronic patch developed by the team could measure blood flow velocities in the range of 1 to 10 mm per second with an error of less than 0.12 mm/s, and vessel depths in the range of 1 to 2 mm with an error of less than 0.07 mm. This level of precision, with errors smaller than the thickness of a human hair, is difficult to achieve with conventional wearable devices.

Notably, when this technology is combined with the photoplethysmography (PPG) sensor used in smartwatches, it can reduce blood pressure measurement error by up to 72.6%. This means that blood pressure readings from smartwatches can get much closer to those from hospital equipment—a significant result that enhances the reliability of wearable devices.

The wireless electronic patch can also be used to detect real-time changes in patient status in emergency medical settings. According to the research team, it can be applied to personalized health management for patients with hypertension and diabetes, as well as for early detection of acute warning signs such as shock.

Professor Kwon said, "The wireless electronic patch technology developed by our team is a fundamental platform for more accurate measurement of blood flow and blood pressure," adding, "By combining it with smartwatches, we expect it will help take everyday health monitoring to the next level."

Meanwhile, Youngmin Sim, an integrated master's and doctoral student, participated as the first author of this research. The results of the study (paper) were published in the international journal Science Advances on February 6.

This content was produced with the assistance of AI translation services.