Ion‐Driven Interfacial Engineering of MXene–Polyacrylamide Hydrogels for Advanced Wearable Electrocardiography and AI‐Driven Blood Pressure Monitoring
MXene (Ti 3 C 2 T x )‐based hydrogels hold great promise for wearable bioelectronics but are limited by unstable interlayer spacing, poor mechanical resilience, and inadequate skin compatibility. An ion‐driven interfacial engineering strategy is introduced that stabilizes Ti 3 C 2 T x nanosheets via Ca 2+ intercalation and Cl − electrostatic screening, expanding interlayer spacing and enabling ultrafast gelation (<5 min). The resulting Ti 3 C 2 T x −polyacrylamide hydrogel exhibits ultrastretchability (2920%), high conductivity (0.39 s m −1 ), and ≈99% cell viability, surpassing existing MXene and commercial hydrogels in terms of cytocompatibility, durability, and skin adherence. Molecular dynamics simulations reveal dynamic interlayer adaptability (6.2–8.2 Å) and ion transport mechanisms that underpin strain‐adaptive sensing and stability across a temperature range of –20 to 40 °C. Integrated into wearable electrodes, the hydrogel enables high‐quality electrocardiography (ECG) acquisition across diverse skin types, achieving signal‐to‐noise ratios of up to 27.2 dB without the need for auxiliary treatments. Coupled with a convolutional neural network–bidirectional gated recurrent unit model trained on ECG data from 17 subjects, the system delivers real‐time, cuffless blood pressure estimation with MAE ± SD of 2.91 ± 3.03 mmHg (systolic blood pressure) and 2.36 ± 2.33 mmHg (diastolic blood pressure), meeting Association for the Advancement of Medical Instrumentation and British Hypertension Society standards. This synergistic material and AI framework establishes a new paradigm for smart, long‐term cardiovascular monitoring.
Authors
- Syed Bilal Ahmed (ORCID: https://orcid.org/0000-0001-5568-3185)
- Bee Luan Khoo (ORCID: https://orcid.org/0000-0003-1100-9994)
- Bilawal Khan (ORCID: https://orcid.org/0000-0002-9877-0104)
- Bangul Khan (ORCID: https://orcid.org/0000-0001-5924-1667)
- Junchen Liao (ORCID: https://orcid.org/0000-0002-5820-3500)
- Iyappan Gunasekaran
- Wasim Khan (ORCID: https://orcid.org/0000-0002-1884-4557)
- Rafi U Shan Ahmad
- Mohamed Elhousseini Hilal
- Md. Shohidul Islam
Institutions
- Department of Health (CN)
- City University of Hong Kong (HK)
- Yango University (CN)
Publication Details
- Journal
- Small Science
- Published
- 2026-03-28
- DOI
- https://doi.org/10.1002/smsc.202500526
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00