Wireless, battery-free, multifunctional integrated bioelectronics for respiratory pathogens monitoring and severity evaluation

Hu Li, Huarui Gong, Tsz Hung Wong, Jingkun Zhou, Yuqiong Wang, Long Lin, Ying Dou, Huiling Jia, Xingcan Huang, Zhan Gao, Rui Shi, Ya Huang, Zhenlin Chen, Wooyoung Park, Ji Yu Li, Hongwei Chu, Shengxin Jia, Han Wu, Mengge Wu, Yiming Liu, Dengfeng Li, Jian Li, Guoqiang Xu, Tianrui Chang, Binbin Zhang, Yuyu Gao, Jingyou Su, Hao Bai, Jie Hu, Chun Ki Yiu, Chenjie Xu, Wenchuang Hu (), Jiandong Huang (), Lingqian Chang () and Xinge Yu ()
Additional contact information
Hu Li: City University of Hong Kong
Huarui Gong: Chinese Academy of Sciences
Tsz Hung Wong: City University of Hong Kong
Jingkun Zhou: City University of Hong Kong
Yuqiong Wang: Beihang University
Long Lin: Peking University
Ying Dou: University of Hong Kong
Huiling Jia: City University of Hong Kong
Xingcan Huang: City University of Hong Kong
Zhan Gao: City University of Hong Kong
Rui Shi: City University of Hong Kong
Ya Huang: City University of Hong Kong
Zhenlin Chen: City University of Hong Kong
Wooyoung Park: City University of Hong Kong
Ji Yu Li: City University of Hong Kong
Hongwei Chu: City University of Hong Kong
Shengxin Jia: City University of Hong Kong
Han Wu: Beihang University
Mengge Wu: City University of Hong Kong
Yiming Liu: City University of Hong Kong
Dengfeng Li: City University of Hong Kong
Jian Li: City University of Hong Kong
Guoqiang Xu: City University of Hong Kong
Tianrui Chang: Beihang University
Binbin Zhang: City University of Hong Kong
Yuyu Gao: City University of Hong Kong
Jingyou Su: City University of Hong Kong
Hao Bai: Sichuan University
Jie Hu: Sichuan University
Chun Ki Yiu: City University of Hong Kong
Chenjie Xu: City University of Hong Kong
Wenchuang Hu: Sichuan University
Jiandong Huang: Chinese Academy of Sciences
Lingqian Chang: Beihang University
Xinge Yu: City University of Hong Kong

Nature Communications, 2023, vol. 14, issue 1, 1-13

Abstract: Abstract The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional pathogenic infection diagnosis system (PIDS) for diagnosing SARS-CoV-2 infection and symptom severity by blow and breath within 110 s and 350 s, respectively. The accuracies reach to 100% and 92% for evaluating the infection and symptom severity of 42 participants, respectively. PIDS realizes simultaneous gaseous sample collection, biomarker identification, abnormal physical signs recording and machine learning analysis. We transform PIDS into other miniaturized wearable or portable electronic platforms that may widen the diagnostic modes at home, outdoors and public places. Collectively, we demonstrate a general-purpose technology for rapidly diagnosing respiratory pathogenic infection by breath and blow, alleviating the technical bottleneck of saliva and nasopharyngeal secretions. PIDS may serve as a complementary diagnostic tool for other point-of-care techniques and guide the symptomatic treatment of viral infections.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-023-43189-z Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43189-z

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-023-43189-z

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().