News Release

Machine learning enabled reusable adhesion, entangled network‑based hydrogel for long‑term, high‑fidelity EEG recording and attention assessment

Peer-Reviewed Publication

Shanghai Jiao Tong University Journal Center

Machine Learning Enabled Reusable Adhesion, Entangled Network-Based Hydrogel for Long-Term, High-Fidelity EEG Recording and Attention Assessment

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  • A dual-network hydrogel (PGEH) cross-linked via liquid metal induction was developed exhibiting remarkable mechanical properties and skin-temperature-triggered on-demand adhesion capabilities.
  • The PGEH capacitive sensor demonstrates exceptional sensitivity (1.25 kPa), rapid dynamic response (30 ms), and long-term cycling stability (20,000 cycles), enabling precise monitoring of human motion and reliable signal transmission.
  • Low-impedance electrophysiological sensor (310 ohms) maintains 14-day signal fidelity (25.2 dB), paired with machine learning-based attention monitoring (91.38% of accuracy) for real-time cognitive feedback in focus-demanding scenarios.
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Credit: Kai Zheng, Chengcheng Zheng, Lixian Zhu, Bihai Yang, Xiaokun Jin, Su Wang, Zikai Song, Jingyu Liu, Yan Xiong, Fuze Tian, Ran Cai, Bin Hu.

Flexible electronics just took a quantum leap forward. A joint team from Beijing Institute of Technology and Lanzhou University, led by Prof. Bin Hu and Prof. Ran Cai, published in Nano-Micro Letters, has unveiled a next-generation hydrogel sensor that combines liquid-metal conductivity, reusable skin adhesion, and machine-learning-powered attention decoding—all in one ultrathin patch.

Why the PGEH Patch Is a Breakthrough

  • Skin-Like Stretch & Strength
    The polyacrylamide/gelatin/EGaIn hydrogel (PGEH) stretches to 1 643 % strain, withstands 366 kPa tensile stress, and survives 20 000 compression cycles—matching natural skin mechanics while preserving sensor integrity.
  • Temperature-Smart Adhesion
    Body-heat activation (30–40 °C) triggers reversible bonding with skin at 104 kPa. A 10 °C cold-water rinse releases the patch painlessly—no irritation, no residue, and reusable for >30 cycles.
  • Microvolt-Scale EEG Precision
    Ultra-low impedance (310 Ω at 100 Hz) and a 25.2 dB signal-to-noise ratio allow PGEH to capture microvolt-level EEG signals for 48 h—far surpassing Ag/AgCl electrodes that degrade after 6 h.
  • AI-Driven Attention Assessment
    Coupled with the lightweight EEGNet model, the three-channel headband achieves 91.38 % accuracy in classifying focused, distracted, and fatigued states—opening doors to real-time cognitive feedback in education, healthcare, and high-risk occupations.

From Lab to Life

  • Encrypted Communication: Finger-tap Morse or binary code via capacitance changes—secure, hands-free messaging.
  • Rehabilitation & Diagnostics: Continuous ECG/EMG monitoring for cardiac or muscular disorders with clinical-grade fidelity.
  • Personalized Neurofeedback: Track attention cycles, optimize work-rest schedules, and issue fatigue alerts—all in a soft, comfortable headband.

With its rare blend of mechanical resilience, biocompatibility, and AI integration, the PGEH platform is poised to redefine wearable neuromonitoring—turning everyday accessories into intelligent health guardians.


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