Wearable Graphene-based smart face mask for Real-Time human respiration monitoring

Hossein Cheraghi Bidsorkhi; Negin Faramarzi; Babar Ali; Lavanya Rani Ballam; Alessandro Giuseppe D'Aloia; Alessio Tamburrano; Maria Sabrina Sarto

doi:10.1016/j.matdes.2023.111970

Wearable Graphene-based smart face mask for Real-Time human respiration monitoring

Mater Des. 2023 Jun:230:111970. doi: 10.1016/j.matdes.2023.111970. Epub 2023 May 2.

Authors

Hossein Cheraghi Bidsorkhi^{1

2}, Negin Faramarzi^{1

2}, Babar Ali^{1

2}, Lavanya Rani Ballam^{1

2}, Alessandro Giuseppe D'Aloia^{1

2}, Alessio Tamburrano^{1

2}, Maria Sabrina Sarto^{1

2}

Affiliations

¹ Department of Astronautical, Electrical, and Energy Engineering (DIAEE), Sapienza University of Rome, via Eudossiana 18, 00184 Rome, Italy.
² Research Center for Nanotechnology Applied to Engineering of Sapienza (CNIS), Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy.

Abstract

After the pandemic of SARS-CoV-2, the use of face-masks is considered the most effective way to prevent the spread of virus-containing respiratory fluid. As the virus targets the lungs directly, causing shortness of breath, continuous respiratory monitoring is crucial for evaluating health status. Therefore, the need for a smart face mask (SFM) capable of wirelessly monitoring human respiration in real-time has gained enormous attention. However, some challenges in developing these devices should be solved to make practical use of them possible. One key issue is to design a wearable SFM that is biocompatible and has fast responsivity for non-invasive and real-time tracking of respiration signals. Herein, we present a cost-effective and straightforward solution to produce innovative SFMs by depositing graphene-based coatings over commercial surgical masks. In particular, graphene nanoplatelets (GNPs) are integrated into a polycaprolactone (PCL) polymeric matrix. The resulting SFMs are characterized morphologically, and their electrical, electromechanical, and sensing properties are fully assessed. The proposed SFM exhibits remarkable durability (greater than1000 cycles) and excellent fast response time (∼42 ms), providing simultaneously normal and abnormal breath signals with clear differentiation. Finally, a developed mobile application monitors the mask wearer's breathing pattern wirelessly and provides alerts without compromising user-friendliness and comfort.

Keywords: Graphene and Advanced materials; Piezoresistive sensor; Real-time monitoring; Respiration monitoring; Smart face mask; Wearable sensing device.