“Fitbit for the face” can turn any face mask into a smart monitoring device

Engineers at Northwestern University have developed a new smart sensor platform for face masks. This is called the “Facebit”.

A lightweight 1/4 size sensor called “FaceBit” uses a small magnet to attach to an N95, cloth, or surgical face mask.

Not only can you sense your real-time respiratory rate, heart rate, and how long you wear the mask, but you may also be able to replace the tedious test by measuring the fit of the mask. All this information is sent wirelessly to the smartphone app, which includes a dashboard for real-time health monitoring. The app can immediately alert the user if problems such as elevated heart rate or mask leaks occur unexpectedly. Physiological data can also be used to predict fatigue, physical health and emotional status.

While a small battery powers the device, FaceBit is designed to collect energy from a variety of ambient energy sources, including the power of the user’s breathing, the user’s breathing and the heat from the sun. This will extend the battery life of the sensor and increase the time between charges.

“We wanted to design an intelligent face mask for medical professionals that wouldn’t have to be inconveniently connected in the middle of a shift,” says Northwestern University. Josiah Hester, Who led the device development? “We have increased the energy of the battery by 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 The study was published last week Minutes of ACM on interactive, mobile, wearable and ubiquitous technology. In this study, FaceBit’s accuracy was similar to clinical-grade devices, and the battery lasted more than 11 days between charges. For more information, please visit the following URL: facebit.health..

Hester is an assistant professor of computer science, computer engineering, and electrical engineering, and a Breed Junior Professor of Design at Northwestern’s. Robert R. McCormick..

Fit test approximation

Before designing FaceBit, Hester and his collaborators first interviewed doctors, nurses, and medical assistants to better understand the need for smart face masks. In a series of studies, all clinicians pointed out that the quality of the mask’s fit is paramount. This is especially true when dealing directly with patients with viral infections.

Healthcare professionals regularly undergo a 20-minute “fit test” to ensure that the N95 mask is properly sealed on the face. During this process, healthcare professionals first wore an N95 respirator, followed by a clear hood over the entire head. Another worker then sends a sweet or bitter aerosol mist into the hood. The concentration of aerosol gradually increases in the hood until it can be detected by the person wearing the respiratory system. If the wearer has a bitter or sweet taste in front of a certain number of aerosol pumps, the mask is not properly sealed.

Wearing the mask for more than 12 hours may cause your face to become numb. You may not notice that the mask is loose.“

Hester’s FaceBit can’t yet replace this tedious process that has long been a challenge in the medical industry, but it can guarantee that the mask fits properly between test events. For example, FaceBit can alert the wearer if the mask becomes loose throughout the day or if the user hits the mask during an activity.

“Wearing a mask for more than 12 hours can cause your face to become numb,” says Hester. “You may not notice that the mask is loose, because you can’t feel the mask or it’s burned out too much and you don’t notice it. By measuring the mask resistance, you can estimate the fit test process. Sudden drop indicates that a leak has occurred and can warn the wearer. “

Face-centered biosensing

But FaceBit can evaluate more than just a mask fit — it can also monitor the person wearing the mask in real time. FaceBit collects various physiological signals such as heart rate and respiratory rate to help the wearer better understand his body and make beneficial health decisions. All health information, including mask fit and wearing time, is displayed in the included smartphone app.

According to Hester, each time a person’s heart beats, their heads move a small amount before they know it. FaceBit can detect its subtle movements and distinguish them from other movements in order to calculate your heart rate.

“Your heart is pushing a lot of blood through your body and it has a very strong ballistic force,” Hester said. “I could feel the power as the blood moved up the major arteries to the face.”

Stressful events can provoke physiological responses such as rapid breathing, and FaceBit can use that information to warn users to take a break, walk, or take a deep breath to calm down. Hospital systems can also use this data to optimize employee shift and break schedules. Also, heart rate and respiratory rate are so closely intertwined that easy monitoring of both may open up new research possibilities.

A future without batteries

Hester, an expert in sustainable battery-free technology, hopes that his team and others will eventually be able to make FaceBit completely battery-free. The wearer’s breathing and movement, or the sun, can now extend battery life. However, in the future, the collected thermal and kinetic energy alone will be able to power the device.

His team evaluated volunteer devices in real-world scenarios, but Hester said FaceBit still needs to undergo clinical trials and validation. The team released the project as open source and open hardware, allowing others to build and validate the device.

“FaceBit provides a first step towards practical face sensing and reasoning, and is sustainable and convenient for monitoring the general health of COVID-19 frontline workers and beyond. We offer comfortable options, “Hester said. “I’m very happy to give this to the research community and see what they can do with it.”

The project “FaceBit: Smart Face Masks Platform” was supported by a grant from the National Science Foundation for rapid response research to address the COVID-19 pandemic (Prize No. CNS-2032408).