Conductive Yarns with Core-Yarn-Count-Controlled Performance for Intelligent Fall Detection Systems

Abstract

In an era of rapid advancements in wearable monitoring systems, the development of high-performance yarn sensors is of great importance for smart textile applications. In this study, the influence of core-yarn diameter on the mechanical and sensing performance of wrapped-yarn sensors was systematically investigated. A viscoelastic model incorporating a Newtonian viscous element was established to describe the mechanical response and interfacial interaction within the wrapped-yarn structure. Experimental results demonstrate that reducing the core-yarn diameter decreases the viscous resistance associated with interfacial friction and improves the deformation responsiveness of the sensor. The optimized yarn sensor exhibits a sensitivity coefficient of 0.2 over a strain range of 0–100% and maintains a stable resistance response during repeated deformation. After 1000 consecutive loading–unloading cycles at 30% strain, the sensor retained a stable electrical response without significant signal attenuation. Furthermore, the optimized sensor was integrated into a knee brace to monitor dynamic knee-joint movements, and distinct resistance responses were obtained during walking, stair climbing, and simulated falling. These results demonstrate the potential of core-yarn structural regulation for improving the mechanical and sensing performance of flexible yarn sensors and provide a feasible approach for wearable knee-motion monitoring and fall-related motion assessment.