Nanomesh Reinforced Eutectogel by Interfacial Engineering for Human Motion Monitoring and Machine Learning-Enabled Gesture Recognition

Engineering soft conductors that simultaneously offer high strength, extreme stretchability, and environmental stability remains a central challenge for next-generation wearable electronics. Here, we incorporate an electrospun polyurethane (PU) nanomesh rich in hydrogen bonding sites into a eutectogel matrix. Benefiting from designable interfacial interactions, the thin hybrid gel (≈45 µm) exhibits high tensile strength (12.6 MPa), remarkable stretchability (1376%) and fatigue resistance. Based on its good sensitivity, the hybrid gel can serve as a strain sensor for wide range human motion monitoring, as well as a multifunctional sensor for humidity and temperature detection. Moreover, its high water vapor transmission rate (1176 g·m −2 ·d −1 ) and robust anti-freezing and anti-drying properties enable reliable recording of physiological signals such as electromyography (EMG) and electrocardiography (ECG). By coupling the EMG output with a convolutional neural network (CNN), the system attains a high gesture recognition accuracy of 98.7%. This work demonstrates great potential for next-generation wearable healthcare and human-machine interfaces.