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Asymmetric Wettability Hydrogel Surfaces for Enduring Electromyographic Monitoring
Jiahao Wu1, Jiabao Xian1, Chaofan He1
1College of Chemistry and Materials Science, Guangdong Provincial Key Laboratory of Speed Capability Research, Su Bingtian Center for Speed Research and Training, Jinan University, Guangzhou, 510632, China.
Advanced Materials (Deerfield Beach, Fla.)
|August 13, 2024
Summary
This study introduces a novel Janus hydrogel for improved surface electromyography (EMG) signal acquisition. The new material ensures durable adhesion and high-fidelity EMG readings, even in sweaty conditions, advancing wearable healthcare technology.
Area of Science:
- Materials Science
- Biomedical Engineering
- Surface Chemistry
Background:
- Hydrogel electrodes are promising for surface electromyography (EMG) signal acquisition.
- Moisture and perspiration can cause hydrogel electrode detachment from skin.
- Achieving integral Janus hydrogels with uniform properties remains challenging.
Purpose of the Study:
- To develop a surface induction strategy for creating hydrophobic/hydrophilic Janus hydrogel surfaces.
- To achieve durable adhesion and high-fidelity EMG signal acquisition in challenging environments.
- To enable advanced applications in digital healthcare and human-machine interaction.
Main Methods:
- A surface induction strategy using hydrophobic/hydrophilic molds and surfactants.
- Regulation of monomer distribution via hydrophobic interactions.
- Fabrication of integral Janus hydrogels with tunable wettability.
Main Results:
- Demonstrated reversal wettability induction and optional hydrogel surfaces.
- Successfully fabricated integral Janus hydrogels using hydrophilic molds.
- Achieved durable conformal adhesion and high-fidelity EMG signals in sweaty conditions due to asymmetric wettability.
Conclusions:
- The developed Janus hydrogel offers a reliable solution for moisture-induced deadhesion issues in EMG electrodes.
- The hydrogel enables quantitative muscle strength description and accurate fatigue assessment.
- Presents a promising candidate for continuous digital healthcare, intelligent human-machine interaction, and the Metaverse.

