Highly Conductive Carbon-Based E-Textile for Gesture Recognition
Xianghui Zeng, Minglu Hu, Pei He, Weikai Zhao, Sihan Dong, Xiaowen Xu, Guozhang Dai, Jia Sun, Junliang Yang
Abstract
Textile, as the most commonly used item in people’s daily life, is the ideal substrate for carrying wearable devices. However, it is difficult to form robust conductive patterns on fabric substrates due to the roughness and porousness of fabric fiber. Here, we used heat transfer printing technology for simple modification of fabric substrate, which reduces the surface roughness of textile substrate. A pure carbon based wearable electronic textile (e-textile) with high conductivity ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$9.82~\Omega $ </tex-math></inline-formula> /sq) and durability (1000 cycles) was obtained by depositing the mixed ink of graphene and carbon nanotubes through screen printing process and combining with roller pressing process. The sensor can well reflect the different bending degrees of fingers and work well in waterproof situations. In addition, five sensors were integrated into the fabric glove. The fabricated smart fabric glove combined with machine learning can recognize 8 different gestures with the average accuracy of 96.58%.