Antifreezing, Adhesive, and Ultra-Stretchable Ionogel for AI-Enabled Motion Tracking and Recognition in Winter Sports
Yongjia Yang, Yao An, Zhaoxiang Yang, Bin Fu, Zhiwu Chen, Xinjia Zheng, Beihang Xu, Weiran Shen, Yapei Wang, Yonglin He
Abstract
Motion tracking and recognition are gaining increasing attention in athletes' training for winter sports due to their importance in posture correction and injury prevention. Electronic skin serves as a better candidate compared to vision-based methods. However, the challenges of its application include sensing materials with good stretchability, softness, anti-freeze, non-volatility, and adhesion, and data processing techniques of high intelligence and efficiency. Here, we propose an antifreezing, adhesive, and ultra-stretchable organic ionogel (OIG). Maximum elongation of over 6500% has been obtained for the OIG of the double network, and the mechanical stretchability is retained at temperatures ranging from -50 to 50 °C. Importantly, the multi-sensor system could realize motion "recognition" rather than "perception" with the help of a convolutional neural network.