Underwater-Adhesive, Stretchable Fabric Dry Electrode Based on a Novel Graphene Oxide Aqueous Polyurethane for Electrophysiological Monitoring
Rui Li , Xinyue Liao , Yige Liu , Juyeol Bae , Ronghui Wu , Changhong LINGHU , Xinghua Hong
Advanced Fiber Materials ›› : 1 -16.
Electronic textiles (E-textiles) provide remarkable potential for next-generation personalized healthcare. However, the limitations in skin adhesion, underwater stability, and air permeability severely hinder their broader application, especially in dynamic and aquatic environments during sweating, showering, or underwater conditions. Here, we reported a highly skin-adhesive, underwater-stable, and breathable E-textile enabled by a graphene oxide–aqueous polyurethane (GAWPU) intermolecular network integrated with a macroscopic knitting structure. Mechanical testing on porcine skin demonstrates an exceptional shear adhesion strength (665 kPa), outperforming previously reported E-textile self-adhesive materials. Benefiting from its multi-scale architecture design, the knitted E-textile also exhibits high stretchability (> 300%) together with breathable waterproofness (466 ± 5 mm/s). The intrinsic water resistance and strong adhesiveness of the GAWPU network allow the E-textile to adhere firmly to biological tissues in wet environments, even for under-water scenarios. As a proof of concept, the E-textile is successfully used as a water-resistant electrode sensor for monitoring diverse human electrophysiological signals, such as surface electromyography (sEMG) and electrocardiography (ECG). Moreover, GAWPU's extraordinary biocompatibility and antibacterial properties enable prolonged skin contact without irritation. This E-textile forms a unified platform integrating tissue adhesion, environmental stability, and biosensing, paving the way for deploying textile-based electronics in real-world biomedical and interactive applications.
Electronic textiles / Graphene oxide–aqueous polyurethane / Skin and underwater adhesion / Breathable waterproofness / Electrophysiological signal detection
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Donghua University, Shanghai, China
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