High-performance polydopamine and silver nanoparticle-modified MXene-based hydrogel flexible strain sensors for transfer-learning-assisted handwriting recognition and wrist-movement monitoring

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Hydrogel-based flexible strain sensors show great potential for applications in wearable electronics, human-machine interfaces, and soft robotics. However, it remains challenging to prepare hydrogel sensors with high sensitivities and wide detection ranges. Herein, we report a polydopamine and silver nanoparticle-modified MXene-based hydrogel, namely, MXene/Ag@PDA/P(AA-AM)/SA-Zn (MAPS), which exhibits a high sensitivity (with a gauge factor of 16.64), high stretchability (1100%), and short response time (0.2 s). This hydrogel-based strain sensor can be adhered to the human body surface as a wearable sensor to monitor physiological and motion signals from small to large strains in a comprehensive range (0.2%-750%). Assisted by the ResNet50D algorithm, a new hydrogel-based handwriting recognition system is developed, which is able to recognize the content of handwritten signals with high accuracy (98.6%) and a short recognition time (less than 1 s). Moreover, we design a multi-directional strain sensor consisting of three independent MAPS hydrogel-based sensor units for effectively distinguishing multidimensional wrist movements. This study offers a promising strategy to prepare a high-performance hydrogel-based strain sensor, showing potential applications in the field of intelligent sensing, human-motion monitoring, and human-computer interaction.