TY - JOUR AU - Suo, Jiao AU - Liu, Yifan AU - Wu, Cong AU - Chen, Meng AU - Huang, Qingyun AU - Liu, Yiming AU - Yao, Kuanming AU - Chen, Yangbin AU - Pan, Qiqi AU - Chang, Xiaoyu AU - Leung, Alice Yeuk Lan AU - Chan, Ho‐yin AU - Zhang, Guanglie AU - Yang, Zhengbao AU - Daoud, Walid AU - Li, Xinyue AU - Roy, Vellaisamy A. L. AU - Shen, Jiangang AU - Yu, Xinge AU - Wang, Jianping AU - Li, Wen Jung PY - 2022 DA - August TI - Wide‐bandwidth nanocomposite‐sensor integrated smart mask for tracking multiphase respiratory activities JO - Advanced Science DO - https://doi.org/10.1002/advs.202203565 AB - 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. PB - Wiley UR - http://eprints.gla.ac.uk/277530/ KW - Coronavirus (COVID-19) KW - Digital health and technology ER