E-Tattoos on Your Face Will Now Track How Hard You're Working
Based on facts, either observed and verified firsthand by the reporter, or reported and verified from knowledgeable sources.
Newsweek AI is in beta. Translations may contain inaccuracies—please refer to the original content.
Had a tough day? Soon you'll be able to prove it as researchers have unveiled a groundbreaking way to track when your brain is working too hard—with a face tattoo.
In a study published today in the Cell Press journal Device, scientists introduced a wireless, temporary electronic forehead tattoo that monitors brainwaves to objectively measure mental workload.
Designed to help change the way we monitor cognitive fatigue in high-stakes professions like air traffic control, truck driving and other focus-intensive roles, the tattoo analyses brain activity in real time, detecting how hard you are working.
"Technology is developing faster than human evolution. Our brain capacity cannot keep up and can easily get overloaded," said Nanshu Lu, senior author of the study and professor at the University of Texas at Austin (UT Austin).
"There is an optimal mental workload for optimal performance, which differs from person to person."
The device works by analyzing brain activity (via electroencephalogram, EEG) and eye movements (via electrooculogram, EOG) using ultrathin which are flexible sensors that stick comfortably to the skin.
A picture of the e-tattoo device designed to measure mental strain.
A picture of the e-tattoo device designed to measure mental strain.
Device/Huh et al.
Unlike traditional EEG caps—often bulky and expensive—the e-tattoo offers a compact and cost-effective solution. The full setup, including a battery pack and reusable chips, costs around $200, with each disposable sensor priced at about $20.
"What's surprising is those caps, while having more sensors for different regions of the brain, never get a perfect signal because everyone's head shape is different," said Lu.
"We measure participants' facial features to manufacture personalized e-tattoos to ensure that the sensors are always in the right location and receiving signals."
In initial tests, six volunteers wore the tattoos while performing increasingly difficult memory tasks. The device accurately detected changes in brainwave patterns.
Rising theta and delta waves indicated rising mental load, while a drop in alpha and beta activity pointed to fatigue. The team also trained a machine learning model to predict mental strain, hinting at future applications in real-time cognitive monitoring.
Similar tools to measure mental load do exist, like the NASA Task Load Index which is designed to measure perceived workload during or after the performance of a task. But this requires the user to fill out a survey, making them more subjective and time-consuming. By contrast, the e-tattoo delivers live and objective data.
Currently, the e-tattoo only works on hairless skin but there is work to try and make the device more accessible, combining it with ink that can work on hair and working to make the product useable at home.
"Being low cost makes the device accessible," said author Luis Sentis from UT Austin. "One of my wishes is to turn the e-tattoo into a product we can wear at home."
As AI and robotics play a growing role in modern workplaces, the team behind the e-tattoo believe tools like this will be key to maintaining human well-being in increasingly automated environments.
"We've long monitored workers' physical health, tracking injuries and muscle strain," said Sentis. "Now we have the ability to monitor mental strain, which hasn't been tracked. This could fundamentally change how organizations ensure the overall well-being of their workforce."
Do you have a tip on a science story that Newsweek should be covering? Do you have a question about e-tattoos? Let us know via science@newsweek.com.
Reference
Huh, H., Shin, H., Li, H., Hirota, K., Hoang, C., Thangavel, S., D'Alessandro, M., Feltman, K. A., Sentis, L., & Lu, N. (2025). A wireless forehead e-tattoo for mental workload estimation. Device, 3. https://doi.org/10.1016/j.device.2025.100781
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