Architecture tailoring of smart knitted double face comfortable strain sensors for Intelligent (E-textiles) application

Abstract

Textiles-oriented flexible strain sensors have been attractive in designing intelligent clothing materials to sense the human body postural changes. However, their efficacy towards sensing performance can be tailored through fabrication architectures variation. In this study knitted strain sensors have been engineered using novel double face fabric designs. Filament polyester, and conductive polyamide coated with silver colloidal particles were used to architect sensors. The sensors provide real-time electrical resistance variation as a sensing feature w.r.t mechanical changes happening in them. Two-dimensional strain testing and comfortability evaluations were carried out to ensure sensing performance and comfortable wearing longevity of sensors. Decreasing linking yarn accumulation per unit area increased the strain sensitivity i.e. changing knit stitches with tuck and miss the sensing capability increased 28% and 95%, respectively. Comfortability of sensors had a parabolic trend, decreasing yarn accumulation enhanced comfort up to tuck-linking courses. While increasing the percentage of conductive polyamide in the linking course improved strain sensitivity by 50%. The research presents such double-face intelligent strain sensors as a suitable solution to the long-term wearability of sensors with comfort.