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Plasmonic hot-electron-assisted ultra-stretchable hydrogel electrodes for wearable cardiovascular monitoring and AI-driven predictive analytics

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Abstract

Wearable bioelectronic systems require soft, deformable materials that maintain high electrical conductivity and reliable interfacial charge transport under large mechanical strains. However, most existing hydrogel- or elastomer-based conductors involve trade-offs among mechanical compliance, electrical performance, and long-term biocompatibility, making it challenging to integrate all three properties within a single material platform. Here, we introduce a plasmonic hot-electron-assisted conductive PAM–PEDOT:PSS–Ag hydrogel, engineered to address these multifunctional requirements for continuous cardiovascular monitoring. Silver nanoparticles (Ag NPs) dispersed within the hydrogel matrix generate localised surface plasmon resonance (LSPR) under UV irradiation, producing smooth, spatially uniform heating and hot-electron injection throughout the precursor solution. This synergistic plasmonic heating effect accelerates polymerisation (∼420 s; 0.1167 h), enhances network homogeneity, and lowers interfacial charge-transfer resistance by promoting more ordered PEDOT:PSS chain assembly and improved crosslinking dynamics. As a result, the hydrogel exhibits ultrahigh stretchability (>2000%), stable conductivity (∼328.82 ± 1.78 mS m−1), and intrinsic antibacterial activity (≥99.7%). The material exhibits consistent electromechanical performance from −20 °C to 40 °C, showing tunable strain sensitivity governed by temperature-dependent network mechanics and ionic mobility. When used as epidermal electrodes, the hydrogel enables high-fidelity electrocardiogram (ECG) acquisition (SNR ≈ 25 dB) in human and rodent models. Integrated with machine-learning analytics, the platform supports accurate demographic prediction (96.2%), demonstrating a scalable material-device-data framework for next-generation personalised cardiovascular monitoring. This journal is © The Royal Society of Chemistry, 2026
Original languageEnglish
Pages (from-to)5408-5427
JournalJournal of Materials Chemistry B
Volume14
Issue number17
Online published27 Mar 2026
DOIs
Publication statusPublished - 6 May 2026

Funding

This work was supported by the City University of Hong Kong (7006082, 7020073, 9609332, 9609333, 9678292, 7020110, and 7020002), the Research Grants Council (RGC) (9048206, 9043805, and 8799020), the Hong Kong Center for Cerebro Cardiovascular Health Engineering (COCHE), the Innovation and Technology Commission (PRP/001/22FX), the Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone Shenzhen Park Project (HZQB-KCZYZ2021017), and the Education Bureau Gifted Education Programme (3030780). A grant from the Institute of Digital Medicine, City University of Hong Kong, partially supported the work described in this paper.

Publisher's Copyright Statement

  • This full text is made available under CC-BY-NC 3.0. https://creativecommons.org/licenses/by-nc/3.0/

RGC Funding Information

  • RGC-funded

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