Wrinkle-Enabled Highly Stretchable Strain Sensors for Wide-Range Health Monitoring with a Big Data Cloud Platform

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

[img]
Preview
Text
Finally_Revised_manuscript_Fu.pdf - Accepted Version

Download (947kB) | Preview
Official URL: https://doi.org/10.1021/acsami.0c11705

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
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

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics