Abstract
This study addresses the challenges faced by individuals who are required to wear masks continuously, leading to issues like breathing difficulties, skin irritation, and diminished face recognition accuracy. These problems are particularly pronounced among individuals aged 21 to 30 who wear masks for prolonged periods, such as during long-haul travel or work commutes. To mitigate these concerns, we introduce innovative mask designs aimed at enhancing comfort and breathability. The paper focuses on our experimental process, which involves distributing questionnaires and conducting interviews within the target group. By discarding conventional information about medical masks, we emphasize the novel technological solutions and advancements achieved through our mask design approach. This work not only highlights the key features of our mask design but also underscores the practical benefits and outcomes resulting from our innovations.
Similar content being viewed by others
Availability of Data and Materials
The authors confirm that the data supporting the findings of this study are available within the article.
References
Aguirre-Cruz G et al (2020) Collagen hydrolysates for skin protection: oral administration and topical formulation from https://www.mdpi.com/2076-3921/9/2/181
Chauhan A (2020) Decline in PM2.5 concentrations over major cities around the world associated with COVID-19 https://www.sciencedirect.com/science/article/pii/S0013935120305272
Dewi C, Chen R-C (2022) Automatic medical face mask detection based on cross-stage partial network to combat COVID-19. Big Data Cogn Comput 6(4):106
Feng T et al (2021) Towards mask-robust face recognition from https://ieeexplore.ieee.org/document/9607719/authors#authors
Gu Y, Shen J, Chen Y (2019) Poster abstract: know you better: a smart watch based health monitoring system from https://ieeexplore.ieee.org/document/8908636/authors#authors
Hayes RB (2019) PM 2.5 air pollution and cause-specific cardiovascular disease mortality https://academic.oup.com/ije/article/49/1/25/5529269?login=true
Hossain G (2022) Omicron variant of SARS-CoV-2: genomics, transmissibility, and responses to current COVID-19 vaccines. J Med Virol. https://doi.org/10.1002/jmv.27588
Kegkeroglou N, Filntisis PP, Maragos P (2023) Medical face masks and emotion recognition from the body: insights from a deep learning perspective. In: PETRA. pp 69–76
Maniadi A et al (2019) Effect of zinc oxide concentration on the dielectric properties of 3D printed acrylonitrile butadiene styrene nanocomposites from https://ieeexplore.ieee.org/document/8923905/authors#authors
Ossa LA, Rost M, Lorenzini G, Shaw DM, Elger BS (2023) A smarter perspective: learning with and from AI-cases. Artif Intell Med 135:102458
Rahmani MKI, Taranum F, Nikhat R, Farooqi MR, Khan MA (2022) Automatic real-time medical mask detection using deep learning to fight COVID-19. Comput Syst Sci Eng 42(3):1181–1198
Rodríguez-Urrego D (2020) Air quality during the COVID-19: PM2.5 analysis in the 50 most polluted capital cities in the world https://www.sciencedirect.com/science/article/abs/pii/S0269749120337635#!
Siriborvornratanakul T (2023) Advanced artificial intelligence methods for medical applications. In: HCI. pp 329–340
Funding
Not applicable.
Author information
Authors and Affiliations
Contributions
The authors contributed equally to this work.
Corresponding author
Ethics declarations
Conflict of Interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Nangam, P., Puangchuen, P., Thongkerd, K. et al. A Study of Integration of Digital Fiber in Medical Masks for Health Monitoring of Wearers. Trans Indian Natl. Acad. Eng. 9, 129–139 (2024). https://doi.org/10.1007/s41403-023-00433-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41403-023-00433-8