E-Tattoo blood pressure promises continuous and mobile monitoring

Blood pressure is one of the most important indicators of heart health, but it is difficult to measure it frequently and reliably outside of a clinical setting. For decades, cuff devices that tighten around the arm to give a reading have been the gold standard. But now researchers at the University of Texas at Austin and Texas A&M University have developed an electronic tattoo that can be worn comfortably on the wrist for hours and provides continuous blood pressure measurements at a level of accuracy nearly exceeding all the options available on the market today.

“Blood pressure is the most important vital sign you can measure, but methods to do it passively outside of the clinic, without a cuff, are very limited,” said Deji Akinwandeprofessor in the Department of Electrical and Computer Engineering at UT Austin and one of the co-leads on the project, which is documented in a new article published today in Nature’s nanotechnology.

High blood pressure can lead to serious heart problems if left untreated. It can be difficult to capture with traditional blood pressure monitoring because it only measures a moment in time, a single data point.

“Taking infrequent blood pressure measurements has many limitations and does not provide an accurate insight into how our bodies are functioning,” said Roozbeh Jafariprofessor of biomedical engineering, computer science and electrical engineering at Texas A&M and the other co-leader of the project.


The continuous monitoring of the e-tattoo makes it possible to measure blood pressure in all kinds of situations: in times of high stress, during sleep, during exercise, etc. It can provide thousands more measurements than any device so far.

Mobile health monitoring has made leaps and bounds in recent years, primarily through technologies such as smartwatches. These devices use metal sensors that get readings based on LED light sources that pass through the skin.

However, major smartwatches are not yet ready for blood pressure monitoring. This is because watches slip on the wrist and can be pulled away from arteries, making it difficult to provide accurate readings. And light-based measurements may falter in people with darker skin and/or larger wrists.

Graphene is one of the strongest and thinnest materials out there, and it’s a key ingredient in electronic tattooing. It is similar to the graphite found in pencils, but the atoms are precisely arranged in thin layers.

Electronic tattoos make sense as a mobile blood pressure monitoring vehicle because they reside in a sticky, stretchy material enveloping the sensors, comfortable to wear for long periods of time, and non-slippery.

“The tattoo sensor is weightless and discreet. You put it there. You don’t even see it and it doesn’t move,” Jafari said. “You need the sensor to stay in the same place because if you move it the measurements will be different.”

The device takes its measurements by sending an electrical current through the skin and then analyzing the body’s response, known as bioimpedance. There is a correlation between bioimpedance and changes in blood pressure related to changes in blood volume. However, the correlation isn’t particularly obvious, so the team had to create a machine learning model to analyze the connection to get accurate blood pressure readings.

In medicine, cuffless blood pressure monitoring is the “holy grail,” Jafari said, but there is no viable solution on the market yet. It’s part of a bigger push in medicine to use technology to disconnect patients from machines while collecting more data wherever they are, allowing them to go from room to room, clinic to clinic and always on. get personalized care.

“All of this data can help create a digital twin to model the human body, to predict and show how it might react and respond to treatments over time,” Akinwande said.

Project team members include Dmitry Kireev and Neelotpala Kumar of UT Austin’s Department of Electrical and Computer Engineering; Kaan Sel and Bassem Ibrahim of the Electrical and Computer Engineering Department of Texas A&M; and Ali Akbari of Texas A&M’s Department of Biomedical Engineering. The research was supported by grants from the Office of Naval Research, the National Science Foundation, and the National Institutes of Health.

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