A lightweight, quarter-sized sensor uses a tiny magnet to attach to any N95, cloth or surgical face mask, say the scientists, and can detect the user’s real-time respiration rate, heart rate and mask wear time. It may also be able to replace cumbersome tests by measuring mask fit.

Information received by the sensor is wirelessly transmitted to a smartphone app, which contains a dashboard for real-time health monitoring. According to the scientists, the app can immediately alert the user when issues, such as elevated heart rate or a leak in the mask, unexpectedly arise. The data could also be used to predict fatigue, physical health status, and emotional state.

Energy harvesting

Although a tiny battery powers the device, FaceBit is designed to harvest energy from a variety of ambient sources – including the force of the user’s breathing and motion, the heat from their breath, as well as from the sun. This is said to extend the sensor’s battery life, lengthening time between charges.

“We wanted to design an intelligent face mask for healthcare professionals that doesn’t need to be inconveniently plugged in during the middle of a shift,” said Northwestern’s Josiah Hester, who led the device development. “We augmented the battery’s energy with energy harvesting from various sources, which means that you can wear the mask for a week or two without having to charge or replace the battery.”

The research was published earlier this month in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. In the study, researchers found FaceBit’s accuracy was similar to clinical-grade devices, and the battery lasted longer than 11 days between charges. 

Josiah Hester, an assistant professor of computer science, computer engineering and electrical engineering, and the Breed Junior Professor of Design at Northwestern’s McCormick School of Engineering, teamed up with colleagues to interview doctors, nurses and medical assistants so they could gain a better understanding of their needs for smart face masks.

In a series of surveys, all clinicians indicated that quality of mask fit was most important – especially when working directly with patients with viral infections.

Although FaceBit cannot yet replace the awkward mask-fit checking process, the engineers say it can ensure the mask retains proper fit between testing events. If the mask becomes loose throughout the day or if the user bumps the mask during an activity, for example, FaceBit can alert the wearer.

“If you wear a mask for 12 hours or longer, sometimes your face can become numb,” Hester explained. “You might not even realise that your mask is loose because you cannot feel it, or you are too burnt out to notice. We can approximate the fit-testing process by measuring mask resistance. If we see a sudden dip in resistance, that indicates a leak has formed, and we can alert the wearer.”

Face-centric bio-sensing

By gathering various physiological signals, FaceBit can also help wearers better understand their own bodies in order to make beneficial health decisions. All health information, including mask fit and wear time, are displayed on the accompanying smartphone app.

According to Hester, every time a person’s heart beats, their head moves an imperceptibly tiny amount. FaceBit can apparently sense that subtle motion and differentiate it from other motions to calculate heart rate.

“Your heart is pushing a lot of blood through the body, and the ballistic force is quite strong,” Hester said. “We were able to sense that force as the blood travels up a major artery to the face.”

Because stressful events can elicit physiological responses, including rapid breathing, FaceBit can use that information to alert the user to take a break, go for a walk, or take some deep breaths to calm down. Hospital systems could use this data to optimise shift and break schedules for its workers.

Although his team evaluated the device on volunteers in real-world scenarios, Hester said FaceBit still needs to undergo clinical trials and validation. The team released the project as open source and open hardware, so others can build and validate the device.

“FaceBit provides a first step toward practical on-face sensing and inference, and provides a sustainable, convenient, comfortable option for general health monitoring for Covid-19 frontline workers and beyond,” Hester said. “I’m really excited to hand this off to the research community to see what they can do with it.”

The project, ‘FaceBit: Smart Face Masks Platform’, was supported by the National Science Foundation’s Grants for Rapid Response Research for addressing the Covid-19 pandemic.