Yarn

Abstract: Smart yarns and textiles are an active field of researches nowadays due to their potential applications in flexible and stretchable electronics, wearable devices, and electronic sensors. Integration of ordinary yarns with conductive fillers renders the composite yarns with new intriguing functions, such as sensation and monitoring of strain and stress. Here we report a low cost scalable fabrication for highly reliable, stretchable, and conductive composite yarn as effective strain sensing material for human motion monitoring. By incorporating highly conductive single-wall carbon nanotubes (SWCNTs) into the elastic cotton/polyurethane (PU) core-spun yarn through a self-designed coating approach, we demonstrated that the yarn is able to detect and monitor the movement of human limbs, such as finger and elbow, and even the wink of eyes. By virtue of the covered structure of the cotton/PU yarn and the reinforcement effect of SWCNTs, the composite yarn can bear up to 300% strain and could be cycled nearly 300,...

Abstract: Smart textiles using fabric-based sensors to monitor gesture, posture or respiration have been exploited in many applications. Most of fabric-based sensors were fabricated by either coating piezo-resistive materials on a fabric or directly knitting conductive fibers into fabrics. Obviously, structures of textiles, including yarn structure and fabric structure, will affect the performances of sensors. However, researches on the effects of the structures have not been explored yet. In this paper, yarn-based sensors were fabricated by using piezo-resistive fibers, elastic, and regular polyester fibers. Single and double wrapping methods were employed to fabricate the yarn-based sensors. Performances of the designed yarn-based sensors were evaluated by measuring their resistance changes under variable loading. It is shown that slippage occurs between the piezo-resistive fibers and the core fibers. The relationship of the resistance versus the strain cannot be described as a linear function and should be modeled as a second order equation. Due to the symmetric structure, the double wrapping yarn could resist the slippage and higher linearity in the resistance curve can be provided. Thus it can be served as a better sensing element. The study also investigates the issue of the twist per meter (TPM) and finds that there are no significant effects for using different TPM. Finally, experiments were conducted on a respiration monitoring system to prove the feasibility of the yarn-based sensors and the results demonstrate that the yarn-based sensor can track the respiratory signals precisely.