TY - JOUR
T1 - An Intelligent Wearable Filtration System for Health Management
AU - Shi, Shuo
AU - Si, Yifan
AU - Li, Zihua
AU - Meng, Shuo
AU - Zhang, Shuai
AU - Wu, Hanbai
AU - Zhi, Chuanwei
AU - Io, Weng Fu
AU - Ming, Yang
AU - Wang, Dong
AU - Fei, Bin
AU - Huang, Haitao
AU - Hao, Jianhua
AU - Hu, Jinlian
N1 - Funding Information:
The authors would like to acknowledge the financial support from the National Natural Science Foundation of China (NSFC) with the title of “Study of high performance fiber to be achieved by mimicking the hierarchical structure of spider-silk”, Grant No. 52073241; “Study of multi-responsive shape memory polyurethane nanocomposites inspired by natural fibers”, Grant No. 51673162; “Developing spider-silk-model artificial fibers by a chemical synthetic approach”, Grant No. 15201719; the Startup Grant of CityU with the title of “Laboratory of wearable materials for healthcare”, Grant No. 9380116; and the Contract Research with the title of “Development of breathable fabrics with nano-electrospun membrane”, CityU ref.: 9231419.
Publisher Copyright:
© 2023 American Chemical Society
PY - 2023/4/11
Y1 - 2023/4/11
N2 - To develop intelligent wearable protection systems is of great significance to human health engineering. An ideal intelligent air filtration system should possess reliable filtration efficiency, low pressure drop, healthcare monitoring function, and man-machine interactive capability. However, no existing intelligent protection system covers all these essential aspects. Herein, we developed an intelligent wearable filtration system (IWFS) via advanced nanotechnology and machine learning. Based on the triboelectric mechanism, the fabricated IWFS exhibits a long-lasting high particle filtration efficiency and bacteria protection efficiency of 99% and 100%, respectively, with a low-pressure drop of 5.8 mmH2O. Correspondingly, the charge accumulation of the optimized IWFS (87 nC) increased to 3.5 times that of the pristine nanomesh, providing a significant enhancement of the particle filtration efficiency. Theoretical principles, including the enhancement of the β-phase and the lower surface potential of the modified nanomesh, were quantitatively investigated by molecular dynamics simulation, band theory, and Kelvin probe force microscopy. Furthermore, we endowed the IWFS with a healthcare monitoring function and man-machine interactive capability through machine learning and wireless transmission technology. Crucial physiological signals of people, including breath, cough, and speaking signals, were detected and classified, with a high recognition rate of 92%; the fabricated IWFS can collect healthcare data and transmit voice commands in real time without hindrance by portable electronic devices. The achieved IWFS not only has practical significance for human health management but also has great theoretical value for advanced wearable systems.
AB - To develop intelligent wearable protection systems is of great significance to human health engineering. An ideal intelligent air filtration system should possess reliable filtration efficiency, low pressure drop, healthcare monitoring function, and man-machine interactive capability. However, no existing intelligent protection system covers all these essential aspects. Herein, we developed an intelligent wearable filtration system (IWFS) via advanced nanotechnology and machine learning. Based on the triboelectric mechanism, the fabricated IWFS exhibits a long-lasting high particle filtration efficiency and bacteria protection efficiency of 99% and 100%, respectively, with a low-pressure drop of 5.8 mmH2O. Correspondingly, the charge accumulation of the optimized IWFS (87 nC) increased to 3.5 times that of the pristine nanomesh, providing a significant enhancement of the particle filtration efficiency. Theoretical principles, including the enhancement of the β-phase and the lower surface potential of the modified nanomesh, were quantitatively investigated by molecular dynamics simulation, band theory, and Kelvin probe force microscopy. Furthermore, we endowed the IWFS with a healthcare monitoring function and man-machine interactive capability through machine learning and wireless transmission technology. Crucial physiological signals of people, including breath, cough, and speaking signals, were detected and classified, with a high recognition rate of 92%; the fabricated IWFS can collect healthcare data and transmit voice commands in real time without hindrance by portable electronic devices. The achieved IWFS not only has practical significance for human health management but also has great theoretical value for advanced wearable systems.
KW - electrostatic enhancement
KW - intelligent wearables
KW - machine learning
KW - nanotechnology
KW - smart mask
UR - http://www.scopus.com/inward/record.url?scp=85151342550&partnerID=8YFLogxK
U2 - 10.1021/acsnano.3c02099
DO - 10.1021/acsnano.3c02099
M3 - Journal article
C2 - 36994837
AN - SCOPUS:85151342550
SN - 1936-0851
VL - 17
SP - 7035
EP - 7046
JO - ACS Nano
JF - ACS Nano
IS - 7
ER -