KAIST Develops AI-Powered Wearable Patch for Real-Time Blood Flow Monitoring
- Yul So
- 5 days ago
- 2 min read
Mar 9, 2026
Yul So
Researchers at the Korea Advanced Institute of Science and Technology have developed a wireless wearable device that can measure blood flow in real time simply by attaching a small electronic patch to the skin. The system combines multilayer thermal sensing with artificial intelligence to achieve medical level accuracy without invasive procedures.
The research team, led by Professor Kwon Kyungha from the Department of Electrical Engineering, designed a method that places temperature sensors at different depths inside the patch. By analyzing how heat moves through the skin, the device can detect information about nearby blood vessels. A deep learning algorithm then processes the complex temperature patterns and separates two key measurements at the same time: blood flow speed and the depth of the blood vessel.
Traditional wearable devices often struggle to measure blood flow accurately because body heat distribution can be complicated. The new system uses AI to distinguish between normal temperature variations and signals created by moving blood, allowing it to produce precise, real-time results.
In laboratory tests, the patch measured blood flow speeds ranging from 1 to 10 millimeters per second with an error of less than 0.12 millimeters per second. It also estimated blood vessel depths between 1 and 2 millimeters with an error of only 0.07 millimeters. According to the researchers, this level of accuracy is smaller than the thickness of a human hair and is difficult to achieve with typical wearable devices.
The technology could be useful in many medical situations. Doctors may use it to monitor patients during emergencies, detect early warning signs of shock, or track health conditions such as hypertension and diabetes.
Professor Kwon said the system could eventually be combined with smartwatches, making advanced blood flow monitoring possible in everyday life and improving personal healthcare management.
