A flexible, adhesive and self-healable hydrogel-based wearable strain sensor for human motion and physiological signal monitoring
Shan Xia, Shixin Song, Fei Jia, Guanghui Gao
- 发表年份
- 2019
- 引用次数
- 343
摘要
The advent of hydrogel-based strain sensors has attracted immense research interest in artificial intelligence, wearable devices, and health-monitoring systems. However, the integration of the synergistic characteristics of good mechanical properties, self-adhesiveness, self-healing capability and high strain sensitivity for fabricating hydrogel-based strain sensors is still a challenge. Here, a multifunctional conductive hydrogel composed of a polyacrylamide (PAAm)/chitosan (CS) hybrid network is fabricated for wearable strain sensors. The PAAm network is cross-linked by hydrophobic associations, and the CS network is ionically cross-linked by carboxyl-functionalized multi-walled carbon nanotubes (c-MWCNTs). These two networks are further interlocked by physical entanglement and hydrogen bond interactions. The obtained hydrogels exhibit excellent flexibility, puncture resistance and self-healing capability because of the efficient energy dissipation of the dynamic cross-linking network. Moreover, the hydrogels exhibit self-adhesive behavior on various materials, including polytetrafluoroethylene, wood, glass, aluminum, rubber and skin. Notably, the hydrogels can be applied as soft human-motion sensors for real-time and accurate detection of both large-scale and small human activities, including joint motions, speaking, breathing, and even subtle blood pulsation. Therefore, it is anticipated that the flexible, self-adhesive, self-healing and conductive hydrogel-based strain sensor will have promising applications in artificial intelligence, soft robots, biomimetic prostheses, and personal health care.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992