Hydrogel sensors have significant application value in the field of artificial intelligence. These sensors combine AI algorithms for data analysis, providing personalized health management solutions and improving medical outcomes. As a new flexible sensing material, hydrogel shows great potential in the field of flexible sensing due to its good biocompatibility and excellent flexibility. However, although hydrogel materials have broad prospects in this field, they still face some inherent limitations, such as poor mechanical properties.

Recently, the field team from the School of Medicine and Bioinformatics Engineering of Northeastern University has made important progress in the field of hydrogel sensors. Inspired by pupae, this research successfully prepared a conductive hydrogel sensor PAB-S with high toughness and low modulus. PAB-S hydrogel has excellent mechanical properties, flexibility, high sensitivity and biocompatibility, as well as frost resistance. By combining the characteristics of PAB-S hydrogel with 2.4G specific communication technology and deep learning (1D-CNN) algorithm, the sensor realizes wireless remote intelligent control, intelligent gesture recognition and finger grasping obstacle recognition based on deep learning. In addition, PAB-S hydrogel also supports man-machine synchronous control of the mechanical arm, opening up new possibilities for medical rehabilitation and man-machine cooperation applications. The sensor based on PAB-S hydrogel shows a broad application prospect in the fields of deep learning, intelligent sensing, medical rehabilitation and human-computer cooperation.

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