Liquid Metal-Based Epidermal Flexible Sensor for Wireless Breath Monitoring and Diagnosis Enabled by Highly Sensitive SnS2 Nanosheets

Author:

Huang Yifan123,Yang Fan13,Liu Sanhu2ORCID,Wang Rongguo13ORCID,Guo Jinhong4ORCID,Ma Xing256ORCID

Affiliation:

1. National Key Laboratory of Science and Technology on Advanced Composites in Special Environments, Harbin Institute of Technology, Harbin 150086, China

2. Sauvage Laboratory for Smart Materials, School of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China

3. Shenzhen STRONG Advanced Materials Research Institute Co., Ltd., China

4. School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

5. Shenzhen Key Laboratory of Flexible Printed Electronics Technology, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China

6. Shenzhen Bay Laboratory, No. 9 Duxue Road, Shenzhen 518055, China

Abstract

Real-time wireless respiratory monitoring and biomarker analysis provide an attractive vision for noninvasive telemedicine such as the timely prevention of respiratory arrest or for early diagnoses of chronic diseases. Lightweight, wearable respiratory sensors are in high demand as they meet the requirement of portability in digital healthcare management. Meanwhile, high-performance sensing material plays a crucial role for the precise sensing of specific markers in exhaled air, which represents a complex and rather humid environment. Here, we present a liquid metal-based flexible electrode coupled with SnS2 nanomaterials as a wearable gas-sensing device, with added Bluetooth capabilities for remote respiratory monitoring and diagnoses. The flexible epidermal device exhibits superior skin compatibility and high responsiveness (1092%/ppm), ultralow detection limits (1.32 ppb), and a good selectivity of NO gas at ppb-level concentrations. Taking advantage of the fast recovery kinetics of SnS2 responding to H2O molecules, it is possible to accurately distinguish between different respiratory patterns based on the amount of water vapor in the exhaled air. Furthermore, based on the different redox types of H2O and NO molecules, the electric signal is reversed once the exhaled NO concentration exceeds a certain threshold that may indicate the onset of conditions like asthma, thus providing an early warning system for potential lung diseases. Finally, by integrating the wearable device into a wireless cloud-based multichannel interface, we provide a proof-of-concept that our device could be used for the simultaneous remote monitoring of several patients with respiratory diseases, a crucial field in future digital healthcare management.

Funder

Shenzhen Bay Laboratory

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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