A new smartwatch, being developed by researchers from The University of Texas at Austin and North Carolina State University, will enable continuous monitoring of blood pressure, a key indicator of heart health.
Cardiovascular diseases represent the leading cause of death worldwide, claiming 18 million lives annually, but these conditions often go undetected due to the infrequency of routine medical checkups. Traditional blood pressure monitoring devices, such as cuffs, are cumbersome and not designed for continuous at-home use, leaving a critical gap in health care.
The researchers received a three-year contract from the Advanced Research Projects Agency for Health (ARPA-H), worth up to $2.5 million, to fill that health care gap. The work builds on an electronic tattoo for blood pressure monitoring that the researchers developed four years ago. The new project represents a bold technical leap forward.
"Our goal is to create a wearable device that can monitor blood pressure unobtrusively and with clinical accuracy," said Deji Akinwande, professor in the Chandra Family Department of Electrical and Computer Engineering and Department of Biomedical Engineering and the lead researcher on the project. "This technology has the potential to revolutionize how we manage cardiovascular health, providing individuals and health care providers with the data they need to make informed decisions and take proactive measures."
The project is structured into two phases over three years, with specific milestones and deliverables each year. In Phase 1, the first year, the team will focus on developing the foundational technology, including designing and validating the smartwatch antenna, creating an alpha version of the core chip for measuring the body's signals, and developing initial machine learning algorithms for blood pressure estimation.
Phase 2 includes years 2 and 3. The second year will see the integration of the technology into a smartwatch prototype, complete with a smartphone app for real-time data visualization and analytics. By the third year, the researchers aim to deliver a fully functional smartwatch prototype.
The final product, Smartwatch BP Prototype 3.0, will feature multimodal sensing capabilities, powered by advanced machine learning algorithms and edge computing technology, to correlate blood pressure with other vital signs, human activities, and environmental factors such as temperature and humidity. The smartwatch will be designed to meet the highest industry standards for blood pressure measurement accuracy.
In medicine, cuff-less blood pressure monitoring is a major priority, but a mainstream option has yet to surface. It's part of a larger push in medicine to use technology to untether patients from machines while collecting more data wherever they are, allowing them to move from room to room, clinic to clinic and still receive personalized care.
"This is more than just a smartwatch; it's a tool for empowering individuals to take control of their health," said Hirofumi Tanaka, professor in the College of Education's Department of Kinesiology and Health Education at UT. "By providing continuous, clinically accurate blood pressure monitoring, we can help people identify potential health issues early and take action to prevent them."
The device measures its readings by passing an electrical signal through the skin and then analyzing the body's response, a process known as bioimpedance. There is a correlation between bioimpedance and changes in blood pressure that is related to changes in blood volume. However, the correlation is not particularly obvious, so the team will employ machine learning models to analyze the connection and obtain accurate blood pressure readings.
Unlike other emerging bioimpedance methods that require direct skin contact, the smartwatch will use radio-frequency (RF) waves emitted and received by an antenna integrated into the device. This approach eliminates the need for intimate skin contact, making the device more comfortable and suitable for long-term use.
The researchers have filed an application to patent this technology. They are exploring forming a startup around their work.
"This research provides a pathway to a practical product that millions of people around the world can use," said Yaoyao Jia, an associate professor of electrical and computer engineering at UT. "Our collaboration with AI, hardware and industry leaders will ensure that this technology is not only scientifically sound but also practical and accessible to the public."
In addition to the interdisciplinary UT team, the researchers collaborated with Edgar Lobaton, a professor of electrical and computer engineering at North Carolina State University and an expert on integrating AI and modeling technologies into cyber-physical systems such as health care devices and rehabilitation robots.
