Human motion recognition using SWCNT textile sensor and fuzzy inference system based smart wearable

Abstract

Wearable technology through proper combination of e-textiles and wearable devices is one of the good ways to accomplish the functions required to monitor and recognize human motions in daily life. However, most of the current research was only done in just simple trials without any significant analytical algorithms. This study aims to introduce a complete combination of e-textile stretch sensor based on single-walled carbon nanotube (SWCNTs) and spandex fabric (PET/SP) with fuzzy inference system (FIS) in order to recognize human motions in a realistic applications. The wearing experiments were conducted for different types of human motions in order to examine the feasibility of the FIS model embedded in the sensing system developed. In the research, the performance of the method developed would be evaluated both by characteristics of the fabrication sensor and accuracy in the application.