Fabricating a smart clothing system based on strain-sensing yarn and novel stitching technology for health monitoring

Various yarn-shaped flexible strain sensors have recently been developed. However, research is lacking on additive manufacturing for smart clothing for integrating yarn sensors with commercial garments. Herein, a strain-sensing yarn is sewn into a piece of fabric through a novel stitching technique, and the influence of the stitching method and needle pitch on the sensing performance is investigated using finite element analysis (FEA). The sensing performance could be improved when the sensing yarn is self-locked in the fabric at the needle eyes, and the needle pitch was reduced to 0.5 cm, which is attributed to the enhanced stress and strain concentration. Meanwhile, the composite sensing fabric featured outstanding performance, including a low detection limit (0.1%), rapid response (280 ms), excellent durability (10000 cycles), and high stability (negligible drift and frequency independence). In addition, the remarkable wear resistance, washability, and anti-interference to ambient humidity and perspiration were obtained. Therein, the optimal stitch trace lengths of sensing yarn for detecting elbow motion, breathing, and heartbeats are discussed. Finally, a smart clothing system composed of smart clothing, data acquisition unit, and mobile APP was developed to simultaneously detect human movement and physiological signals. This work provides a reference to produce intelligent garments based on yarn sensors for health monitoring.