Huang, Jian, Zhou, Jian, Luo, Yangmei, Yan, Gan, Liu, Yi, Shen, Yiping, Xu, Yong, Li, Honglang, Yan, Lingbo, Zhang, Guanhua, Fu, Richard and Duan, Huigao (2020) Wrinkle-Enabled Highly Stretchable Strain Sensors for Wide-Range Health Monitoring with a Big Data Cloud Platform. ACS Applied Materials & Interfaces, 12 (38). pp. 43009-43017. ISSN 1944-8244
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Abstract
Flexible and stretchable strain sensors are vital for emerging fields of wearable and personal electronics, but it is a huge challenge for them to possess both wide-range measurement capability and good sensitivity. In this study, a highly stretchable strain sensor with a wide strain range and a good sensitivity is fabricated based on smart composites of carbon black (CB)/wrinkled Ecoflex. The sensor exhibits a maximum recoverable strain of up to 500% and a high gauge factor of 67.7. It has a low hysteresis, a fast signal response (as short as 120 ms), and a high reproducibility (up to 5000 cycles with a strain of 150%). The sensor is capable of detecting and capturing wide-range human activities, from speech recognition and pulse monitoring to vigorous motions. It is also applicable for real-time monitoring of robot movements and vehicle security crash in an anthropomorphic field. More importantly, the sensor is successfully used to send signals of a volunteer’s breathing data to a local hospital in real time through a big data cloud platform. This research provides the feasibility of using a strain sensor for wearable Internet of things and demonstrates its exciting prospect for healthcare applications.
Item Type: | Article |
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Subjects: | H800 Chemical, Process and Energy Engineering |
Department: | Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering |
Depositing User: | Elena Carlaw |
Date Deposited: | 24 Sep 2020 14:53 |
Last Modified: | 28 Aug 2021 03:30 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/44251 |
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