In this interview, News-Medical talks to Professor Seung Hwan Ko about his recent research in which he developed a face mask that can adapt to your changing conditions and environment.
People are used to wearing face masks daily due to the ongoing COVID-19 pandemic. What inspired your research on face masks, and how can they be adapted for better use?
Most face masks invented so far have not been aware of the dynamic change of users’ condition and environment. Instead, most face masks have just focused on increasing filtration efficiency. Although the mask itself has a very high filtration efficiency, this does not mean that it is user-friendly (usually a high-efficiency filter means that the mask is difficult to breathe and uncomfortable).
Under certain conditions, other components are more important than filtration efficiency. For example, last year I read news articles that said several students died during a sports lesson while wearing a mask. This may mean that a single type of filter mask may not respond properly to the dynamically altered condition of the user, and the user should therefore wear different types of face mask and change them depending on their physical needs or changes in the environment.
We tried to invent an AI-powered face mask that detects the user’s condition (predicting short-term change in respiration rate using AI) or detects the change in air quality in the environment and automatically changes the pore size, changing the balance between comfort and filtration efficiency.
Image Credit: Volurol / Shutterstock.com
The main purpose of face masks is to filter out harmful pollutants. How do face masks do this?
Most face masks on the shelf use air filters in fabric where very thin (about 10-100 times thinner than a human hair) fibers wrap each other into a loosely packed sponge-like porous structure. When an air stream passes through the complex, intertwined network of tiny air tunnels, the small airborne particles, which we call pollutants, collide with the fibers and adhere to them. How to filter face masks.
Our invention also shares the same working mechanism in terms of pollutant filtration, but differs greatly in that it allows dynamic tuning of how the mechanism actually works.
Can you describe how face masks are often designed and developed?
Until two years ago, it was true that there was not much interest in face masks because masks were just a sanitary product that was on the fringes of our ordinary lives. However, the global COVID-19 pandemic changed the situation.
Over the past year and even today, countless reports have been made about the development of new, advanced types of face masks, while the majority of them still rely on conventional, passive air filtration technology. As far as we know, our invention is the first ever reported development of a ‘dynamically adjustable face mask’.
Many people find face masks uncomfortable, especially when exercising. Why is it?
When people wear a mask, they find the masks uncomfortable, especially when exercising because the body needs more oxygen and the rate of breathing increases. However, a mask usually induces the pressure drop (or pressure difference) due to the presence of the filter.
The pressure drop (or pressure difference) increases more for the filter with higher efficiency. The higher pressure drop (or pressure difference) makes it difficult for the user to breathe and uses more energy (which makes the user uncomfortable).
Can you describe how you conducted your latest research into designing a face mask that adapts to changing conditions?
Our team is a cooperative coalescence of experts from various engineering fields, ranging from materials science, mechanics, electrical engineering and even machine intelligence. That’s how we’ve been able to develop a usable AI-powered face mask that starts from scratch.
Our team started by coming up with an archetype idea that was a little unclear to see the first time. But the well-educated engineering minds from various facets made it possible to materialize the idea into a tangible, compelling unit. In that sense, we would say that there has been collaborative interdisciplinary technique behind the successful execution of our work.
Image credit: Adapted from ACS Nano 2021, DOI: 10.1021 / acsnano.1c06204
How did you develop your dynamic respirator? How does this air filter work under different conditions?
One of the striking features of our dynamic respirator is that it can automatically transform its filtration characteristics to suit the given circumstance. This means that the system is designed to be able to “register” the environment associated with its operation.
Thus, we donated the sensory capacity to the system by incorporating sensors. A PM sensor (particles) is used to measure how much of the ambient air is polluted, and the barometers are used to sense the wearer’s breathing pattern that reflects the physical condition. The information collected from the sensors is then used to create comprehensive ‘situational awareness’ of the AI algorithm, which then generates the dynamic adjustment of filtering characteristics to the different scenarios.
What benefits will this face mask have for humans compared to other available face masks?
The traditional mask usually has the basic concept that the users have to adapt to the mask (this means that the users have to wear the uncomfortable situation). However, we tried to invent a new concept where the mask adapts to the user’s condition and external environment.
I think our AI-powered mask is the first demonstration considering the dynamic change in user demand and environmental conditions, and it changes the current focus in masks from filters to humans (users) for the first time.
What role did artificial intelligence (AI) play in your research?
What we have tried to build through this work was an automated respirator that can easily adapt to an individual user, necessitating a very personal operating algorithm; the respirator and the algorithm running will figuratively recognize ‘characteristic’ transitions of breathing patterns in a particular user.
The characteristics of how the transition occurs, for example, differ between individuals. This makes the development of a universal algorithm that can be released to the public extremely challenging. In this context, we choose to develop an AI algorithm that learns the breathing properties of individual users to enable ‘universal personalization’, which is not possible with ordinary, inflexible algorithms.
Do you think that if there were easily accessible face masks, more people would wear them regularly and potentially reduce the spread of COVID-19?
The biggest motivation for the AI-powered mask came from my personal experience. When I go to the gym or go out jogging, I feel a strong urge to take off the mask during exercise. I could also see many people putting the mask away while using the running machine. During the COVID-19 situation, many places (indoors or outdoors) have a strict restriction policy on wearing a mask.
The main reason they do not wear the mask is simply that they can be very uncomfortable breathing while wearing it. AI-powered masks automatically adjust the balance between filtering efficiency and comfort to satisfy users’ dynamic state and environmental changes. The customizable face masks are expected to help more people wear masks regularly and potentially reduce the spread of COVID-19.
Image credit: Drazen Zigic / Shutterstock.com
What further research needs to be done before these personalized face masks are readily available?
Miniaturization of the mask and to illuminate the use of the face mask on the market. Technological advances often tend to hide the very technology from our eyes. Light enough, small enough and therefore ignorant technologies can offer pure utility value alone without distracting the user. This philosophy leads our team to discover additional technical capabilities to minimize the entire system and improve the user experience.
What are the next steps in your research?
Along with the miniaturization, we are trying to discover different elastic materials to provide the next level of functionality to the stretchable air filter, an important part of our system. For example, we can make an air filter that can generate even a small amount of electricity due to the mechanical modulation of the air filter.
Or we can focus on self-healing materials to improve the long-term applicability and mechanical stability of the stretchable air filter. Most of all, we expect an active collaboration with medical experts from all corners of the globe to transfer our technology to the industry.
Where can readers find more information?
More detailed information on the AI-powered smart face mask can be found in the recent publication
“Dynamic pore modulation of stretchable air filter for machined learned adaptive respirator”, ACS Nano, in the press, 2021. [doi/10.1021/acsnano.1c06204]
A further related study from our group on the transparent and recyclable filter can be found in our previous publication “High Efficiency, Transparent, Reusable and Active PM2.5 Filters by Hierarchical Ag Nanowire Percolation Network”, Nano Letters, 17, 4339-4346, 2017. [doi/10.1021/acs.nanolett.7b01404]
About Professor Seung Hwan Ko
Seung Hwan Ko is Professor of Applied Nano & Thermal Science (ANTS) Lab, Department of Mechanical Engineering., Seoul National University, Korea. Prior to joining Seoul National University, he had been a faculty member in KAIST, Korea since 2009. He received his Ph.D. degree in mechanical engineering from UC Berkeley in 2006.
He worked as a postdoc at UC Berkeley until 2009. His current research interests are functional filters (variable pore filter, transparent filter, recyclable filter, stretchable filter, antibacterial filter), portable electronics, stretchable / flexible electronics, VR / AR technologies.