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Application of a Dual Upper Limb Task-Oriented Robotic System for the Functional Recovery of the Upper Limb in Stroke Patients
Published on: October 11, 2024
Dual-Network PVA/PAM Hydrogel Strain Sensor for Machine-Learning-Assisted Rehabilitation-Oriented Hand Motion
Wendi Liu1,2, Jintao Wang1, Yuanduo Wang3
1National & Local Joint Engineering Research Center of Technical Fiber Composites for Safety and Health, School of Textile & Clothing, Nantong University, Nantong 226019, China.
Abstract:
Wearable 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.
