Wide‐Bandwidth Nanocomposite‐Sensor Integrated Smart Mask for Tracking Multiphase Respiratory Activities. Issue 31 (23rd August 2022)

• Record Type: Journal Article
• Authors: Suo, Jiao; Liu, Yifan; Wu, Cong; Chen, Meng; Huang, Qingyun; Liu, Yiming; Yao, Kuanming; Chen, Yangbin; Pan, Qiqi; Chang, Xiaoyu; Leung, Alice Yeuk Lan; Chan, Ho‐yin; Zhang, Guanglie; Yang, Zhengbao; Daoud, Walid; Li, Xinyue; Roy, Vellaisamy A. L.; Shen, Jiangang; Yu, Xinge; Wang, Jianping; Li, Wen Jung
• Is Part Of: Advanced science. Volume 9:Issue 31(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-08-23
• Subjects: Covid‐19 -- high‐frequency pressure sensors -- respiratory sounds recognition -- smart masks -- sponge structure sensors; Science -- Periodicals; 505
• DOI: 10.1002/advs.202203565
• Languages: English
• ISSNs: 2198-3844

Abstract

Abstract: Wearing masks has been a recommended protective measure due to the risks of coronavirus disease 2019 (COVID‐19) even in its coming endemic phase. Therefore, deploying a "smart mask" to monitor human physiological signals is highly beneficial for personal and public health. This work presents a smart mask integrating an ultrathin nanocomposite sponge structure‐based soundwave sensor (≈400 µm), which allows the high sensitivity in a wide‐bandwidth dynamic pressure range, i.e., capable of detecting various respiratory sounds of breathing, speaking, and coughing. Thirty‐one subjects test the smart mask in recording their respiratory activities. Machine/deep learning methods, i.e., support vector machine and convolutional neural networks, are used to recognize these activities, which show average macro‐recalls of ≈95% in both individual and generalized models. With rich high‐frequency (≈4000 Hz) information recorded, the two‐/tri‐phase coughs can be mapped while speaking words can be identified, demonstrating that the smart mask can be applicable as a daily wearable Internet of Things (IoT) device for respiratory disease identification, voice interaction tool, etc. in the future. This work bridges the technological gap between ultra‐lightweight but high‐frequency response sensor material fabrication, signal transduction and processing, and machining/deep learning to demonstrate a wearable device for potential applications in continual health monitoring in daily life. Abstract : A "smart mask" is developed by using an ultrathin nanocomposite‐based soundwave sensor with high sensitivity and wide‐bandwidth dynamic range, i.e., integrated with machine/deep learning algorithms, the smart mask can identify breath, two‐/tri‐phase coughs, and speaking words directly. The smart mask could be a new wearable Internet of Things device for personal health monitoring and respiratory disease identification tool in the future.