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Zhao et al. Soft Sci. 2025, 5, 10                                         Soft Science
               DOI: 10.20517/ss.2024.61



               Research Article                                                              Open Access



               Printed graphene/CNTs/TPU-fabric wearable strain

               sensor for healthcare monitoring


                                          1
                                 1,*
                          1
                                                                         1
                                                    1
                                                                  2
               Weikai Zhao , Pei He , Kai Ling , Chen Gao , Kaifeng Wang , Lin Wu , Junliang Yang 2,3,*
               1
                School of Electronic Information, Central South University, Changsha 410083, Hunan, China.
               2
                Hunan Key Laboratory for Super-microstructure and Ultrafast Process, School of Physics, Central South University, Changsha
               410083, Hunan, China.
               3
                FuRong Laboratory, Changsha 410078, Hunan, China.
               * Correspondence to: Dr. Pei He, School of Electronic Information, Central South University, 932 Lushan South Road, Changsha
               410083, Hunan, China. E-mail: pei.he@csu.edu.cn; Prof. Junliang Yang, Hunan Key Laboratory for Super-microstructure and
               Ultrafast Process, School of Physics, Central South University, 932 Lushan South Road, Changsha 410083, Hunan, China. E-mail:
               junliang.yang@csu.edu.cn
               How to cite this article: Zhao, W.; He, P.; Ling, K.; Gao, C.; Wang, K.; Wu, L.; Yang, J. Printed graphene/CNTs/TPU-fabric
               wearable strain sensor for healthcare monitoring. Soft Sci. 2025, 5, 10. https://dx.doi.org/10.20517/ss.2024.61
               Received: 31 Oct 2024  First Decision: 25 Nov 2024  Revised: 1 Jan 2025  Accepted: 2 Jan 2025  Published: 6 Feb 2025
               Academic Editors: Seung Hwan Ko, Carlo Massaroni  Copy Editor: Ting-Ting Hu  Production Editor: Ting-Ting Hu

               Abstract
               Wearable strain sensors hold immense promise in monitoring human motion activities due to their low cost,
               lightweight design, and excellent biocompatibility. For example, continuous real-time monitoring of neck activity
               can effectively prevent the onset of acute torticollis. However, current approaches to monitoring sleep neck
               posture primarily depend on technologies such as computer vision, which are characterized by limited wearability
               and portability issues. Herein, this work introduces a cost-effective, highly sensitive carbon-based strain sensor
               fabricated on a fabric substrate with a printing technique, which is eco-friendly and biocompatible. The proposed
               sensor displays a broad sensing range of 112%, high sensitivity (gauge factor > 210), low sensing limit (~ 0.1 ‰), and
               outstanding long-term stability over 3,000 cycles. The sensor’s utilization in monitoring joint motion, vocal cord
               activity, pulse, and electrocardiogram (ECG) is illustrated. Moreover, a portable system for monitoring neck activity
               and ECG signals while sleeping has been engineered, capable of detecting neck movements and ECG signals during
               sleeping hours. The composite materials design strategy combined with printing techniques provides a potential
               route for high-performance and low-cost wearable strain sensors in health monitoring.

               Keywords: Strain sensors, sleep posture monitoring, multimodal monitoring, wearable system









                           © The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0
                           International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing,
                           adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as
               long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
               indicate if changes were made.

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