High Performance Polydopamine and Silver Nanoparticles Modified MXene-Based Hydrogel Flexible Strain Sensors for Transfer-Learning Assisted Hand-Written Recognition and Wrist Movement Monitoring

Abstract

Hydrogel-based flexible strain sensors show great potentials for applications in wearable electronics, human-machine interfaces, and soft robotics. However, it remains challenging to prepare hydrogel sensors with high sensitivities and wide dection range.Herein, we report a polydopamine and silver nanoparticles modified Mxene-based hydrogel (MAPS) which achieves high sensitivities (with a gauge factor of 16.64), stretchability (1100 %), and fast 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 ResNet50D algorithm, a new hydrogel-based handwriting recognition system is developed, which is able to recognition of handwritten signalscontent with high accuracy (98.6% accuracy) and a fast recognition time (less than 1 s). Moreover, we designed a muliti-directions strain sensor consisting of three independent MAPS hydrogel-based sensor units for effectively distinguishing multidimensional wrist movements. This study offers a promising strategy to prepared high performance hydrogel-based strain sensor, showing potential applications in the field of intelligent sensing, human movement monitoring, human-computer interaction experience.