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-s...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.展开更多
Knitted flexible sensors,owing to their looped architecture,exhibit excellent stretchability,comfort,and responsiveness,enabling real-time monitoring of biomechanical motion.Here,we systematically investigated the ele...Knitted flexible sensors,owing to their looped architecture,exhibit excellent stretchability,comfort,and responsiveness,enabling real-time monitoring of biomechanical motion.Here,we systematically investigated the electromechanical performance of conductive fabrics composed of stainless steel,silver-plated,and copper-plated yarns across rib,half-air layer,and air-layer knitting structures.Among them,copper-plated rib fabrics with(35r×35r)/5 cm density demonstrated superior sensing performance,with stable resistance variation(~2 to~1 kΩfrom 0°to 90°wrist bending),high linearity(R^(2)=0.959),good stability(δ=0.232 after 100 cycles),and a gauge factor(GF)of~2.73.An equivalent resistance model was established to elucidate the impact of loop geometry on sensor performance,confirming that higher coursewise density lowers resistance and enhances sensitivity.A wearable knitted wristband sensor was fabricated that accurately distinguishes wrist postures.These findings highlight the potential of structured conductive knits as customizable,high-performance platforms for next-generation wearable health monitoring and rehabilitation systems.展开更多
基金supported by the Qing Lan Projectthe Third-Priority Academic Program Development of Jiangsu Higher Education Institutions+1 种基金the Science and Technology Guidance Project of China National Textile and Apparel Council(Grant No.2020102)the Primary Research&Development Plan of Jiangsu Province(Grant No.BE2019045)。
文摘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.
基金financial support of the Hubei Integrative Technology and Innovation Center for Advanced Fibrous Materials(XC202501)and Scientific Research Plan Projects of Hubei Provincial Department of Education for the Year 2024(Grant No.B2024466).
文摘Knitted flexible sensors,owing to their looped architecture,exhibit excellent stretchability,comfort,and responsiveness,enabling real-time monitoring of biomechanical motion.Here,we systematically investigated the electromechanical performance of conductive fabrics composed of stainless steel,silver-plated,and copper-plated yarns across rib,half-air layer,and air-layer knitting structures.Among them,copper-plated rib fabrics with(35r×35r)/5 cm density demonstrated superior sensing performance,with stable resistance variation(~2 to~1 kΩfrom 0°to 90°wrist bending),high linearity(R^(2)=0.959),good stability(δ=0.232 after 100 cycles),and a gauge factor(GF)of~2.73.An equivalent resistance model was established to elucidate the impact of loop geometry on sensor performance,confirming that higher coursewise density lowers resistance and enhances sensitivity.A wearable knitted wristband sensor was fabricated that accurately distinguishes wrist postures.These findings highlight the potential of structured conductive knits as customizable,high-performance platforms for next-generation wearable health monitoring and rehabilitation systems.
基金financially supported by the Fundamental Research Funds for the Central UniversitiesHeilongjiang Provincial Natural Science Foundation of China (YQ2020E009)。
