Dual−Network PVA/PAM Hydrogel Strain Sensor for Machine−Learning−Assisted Rehabilitation−Oriented Hand Motion Monitoring
Wendi Liu, Jintao Wang, Yuanduo Wang, Zhangqi Xia, Ruixin Liu, Yixuan Li, Xinyang He, Hailou WangWearable rehabilitation monitoring requires soft strain sensors with mechanical robustness, stable electromechanical responses, and intelligent motion recognition capability. Here, we report a poly(vinyl alcohol)/polyacrylamide (PVA/PAM) double−network hydrogel strain sensor for rehabilitation−oriented wearable monitoring. The hydrogel was prepared by ultraviolet ray (UV)−initiated acrylamide polymerization followed by freeze−thaw−induced PVA crystallization, forming a covalent PAM network interpenetrated with a physically crosslinked PVA network. The resulting hydrogel possessed a compact porous structure, improved stretchability, and stable deformation recovery. The optimized sensor exhibited a tensile strength of approximately 0.52 MPa, an elongation at break of approximately 480%, a response time of 0.12 s, and a recovery time of 0.17 s. It generated repeatable resistance signals under cyclic strain, finger bending, wrist motion, and grip training. Furthermore, the sensor enabled morse−code information transmission and support vector machine (SVM)−based recognition of rehabilitation−related hand states, including straight, bend, and clench. This work provides a soft hydrogel sensing platform for real−time rehabilitation−oriented hand motion, while morse−code encoding provides auxiliary assistance and an emergency communication function.