A flexible, adhesive and self-healable hydrogel-based wearable strain sensor for human motion and physiological signal monitoring
Abstract
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.
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With AI and ML algorithms, wearable devices provide users with personalized health recommendations, early detection of potential issues, and even life-saving interventions.
“With cutting-edge AI and ML algorithms, these devices provide users with personalized health recommendations, early detection of potential issues, and even life-saving interventions [177,183,184,229,230,231].”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [229]
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- Authors
- Xia, S., Song, S., Jia, F., & Gao, G.
- Affiliations
- Advanced Institute of Materials Science (JP)
- Corresponding author
- Jia, Fei
- Gao, Guanghui
- Venue
- Journal of Materials Chemistry B
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2019
- Volume
- 7
- Issue
- 30
- Pages
- 4638-4648
- ISSN
- 2050-750X (ISSN-L)
- 2050-7518
- OpenAlex
- W2955424780
- Cited by
- 349
- References
- 40
- Citations by year
- 2026: 30 · 2025: 47 · 2024: 62 · 2023: 59 · 2022: 57 · 2021: 52 · 2020: 37 · 2019: 5
- FWCI
- 13.29
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Materials Chemistry B (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (51703012, 51873024)
- Department of Science and Technology of Jilin Province (20180101207JC, 20180201021G)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Advanced Sensor and Energy Harvesting Materials
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Medicine › Hydrogels: synthesis, properties, applications
- Physical Sciences › Engineering › Mechanical Engineering › Advanced Materials and Mechanics
- Keywords
- conductive hydrogels, wearable strain sensors, self-healing hydrogels, self-adhesion, polyacrylamide, chitosan, multi-walled carbon nanotubes, hydrophobic association, human motion monitoring, physiological monitoring, soft robotics
- MeSH terms
- Wearable Electronic Devices, Polyacrylamides, Acrylic Resins, Humans, Hydrogen Bonding, Monitoring, Physiologic, Motion, Sprains and Strains, Hydrogels, Chitosan
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