{"title":"用于多功能可穿戴压力监测的芯-鞘石墨烯纱线传感器","authors":"Zhengwei Jia;Xiaoping Lin;Hao Liu","doi":"10.1109/JSEN.2025.3579215","DOIUrl":null,"url":null,"abstract":"To address the demand for high-performance flexible pressure sensors in wearable electronics, this study proposes a fabrication method for graphene-wrapped yarn piezoresistive sensors with a core-sheath structure. Using a stainless-steel sewing thread as the conductive core and graphene-coated conductive nylon monofilament as the functional wrapping layer, the yarn twist parameters (1500–3500 T/m) were optimized through controlled wrapping process to systematically investigate the structure-performance quantitative relationship. Results demonstrate that the 3000-T/m sample exhibits optimal sensitivity in the medium-to-high pressure range (1–25 N; <inline-formula> <tex-math>${S} =0.037$ </tex-math></inline-formula>/N at 25 N), whereas the 2500-T/m sample achieves significantly enhanced sensitivity in low-pressure regime (<1.0> <tex-math>${S} =9.37$ </tex-math></inline-formula>/N at 0.05 N), representing a nearly threefold improvement over its 1500 T/m counterpart (<1.0> <tex-math>${S} =3.12$ </tex-math></inline-formula>/N at 0.05 N). Moreover, the sensor demonstrates broad detection range (0.01–25 N), fast response time (0.4 s), and excellent cycling stability (no degradation after 7000 compression cycles). Through embroidery and weaving techniques, we fabricated finger-joint motion-monitoring gloves, plantar pressure-sensing insoles, and a <inline-formula> <tex-math>$16\\times 16$ </tex-math></inline-formula> sitting posture pressure matrix, validating its multiscale application potential in human motion capture and body pressure monitoring. This work provides a novel strategy for developing highly sensitive and customizable textile-based electronic sensors, advancing the practical implementation of wearable health monitoring technologies.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29744-29751"},"PeriodicalIF":4.3000,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Core-Sheath Graphene Yarn Sensors for Versatile Wearable Pressure Monitoring\",\"authors\":\"Zhengwei Jia;Xiaoping Lin;Hao Liu\",\"doi\":\"10.1109/JSEN.2025.3579215\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To address the demand for high-performance flexible pressure sensors in wearable electronics, this study proposes a fabrication method for graphene-wrapped yarn piezoresistive sensors with a core-sheath structure. Using a stainless-steel sewing thread as the conductive core and graphene-coated conductive nylon monofilament as the functional wrapping layer, the yarn twist parameters (1500–3500 T/m) were optimized through controlled wrapping process to systematically investigate the structure-performance quantitative relationship. Results demonstrate that the 3000-T/m sample exhibits optimal sensitivity in the medium-to-high pressure range (1–25 N; <inline-formula> <tex-math>${S} =0.037$ </tex-math></inline-formula>/N at 25 N), whereas the 2500-T/m sample achieves significantly enhanced sensitivity in low-pressure regime (<1.0> <tex-math>${S} =9.37$ </tex-math></inline-formula>/N at 0.05 N), representing a nearly threefold improvement over its 1500 T/m counterpart (<1.0> <tex-math>${S} =3.12$ </tex-math></inline-formula>/N at 0.05 N). Moreover, the sensor demonstrates broad detection range (0.01–25 N), fast response time (0.4 s), and excellent cycling stability (no degradation after 7000 compression cycles). Through embroidery and weaving techniques, we fabricated finger-joint motion-monitoring gloves, plantar pressure-sensing insoles, and a <inline-formula> <tex-math>$16\\\\times 16$ </tex-math></inline-formula> sitting posture pressure matrix, validating its multiscale application potential in human motion capture and body pressure monitoring. This work provides a novel strategy for developing highly sensitive and customizable textile-based electronic sensors, advancing the practical implementation of wearable health monitoring technologies.\",\"PeriodicalId\":447,\"journal\":{\"name\":\"IEEE Sensors Journal\",\"volume\":\"25 15\",\"pages\":\"29744-29751\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Sensors Journal\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11040142/\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/11040142/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Core-Sheath Graphene Yarn Sensors for Versatile Wearable Pressure Monitoring
To address the demand for high-performance flexible pressure sensors in wearable electronics, this study proposes a fabrication method for graphene-wrapped yarn piezoresistive sensors with a core-sheath structure. Using a stainless-steel sewing thread as the conductive core and graphene-coated conductive nylon monofilament as the functional wrapping layer, the yarn twist parameters (1500–3500 T/m) were optimized through controlled wrapping process to systematically investigate the structure-performance quantitative relationship. Results demonstrate that the 3000-T/m sample exhibits optimal sensitivity in the medium-to-high pressure range (1–25 N; ${S} =0.037$ /N at 25 N), whereas the 2500-T/m sample achieves significantly enhanced sensitivity in low-pressure regime (<1.0> ${S} =9.37$ /N at 0.05 N), representing a nearly threefold improvement over its 1500 T/m counterpart (<1.0> ${S} =3.12$ /N at 0.05 N). Moreover, the sensor demonstrates broad detection range (0.01–25 N), fast response time (0.4 s), and excellent cycling stability (no degradation after 7000 compression cycles). Through embroidery and weaving techniques, we fabricated finger-joint motion-monitoring gloves, plantar pressure-sensing insoles, and a $16\times 16$ sitting posture pressure matrix, validating its multiscale application potential in human motion capture and body pressure monitoring. This work provides a novel strategy for developing highly sensitive and customizable textile-based electronic sensors, advancing the practical implementation of wearable health monitoring technologies.
期刊介绍:
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
-Sensor Phenomenology, Modelling, and Evaluation
-Sensor Materials, Processing, and Fabrication
-Chemical and Gas Sensors
-Microfluidics and Biosensors
-Optical Sensors
-Physical Sensors: Temperature, Mechanical, Magnetic, and others
-Acoustic and Ultrasonic Sensors
-Sensor Packaging
-Sensor Networks
-Sensor Applications
-Sensor Systems: Signals, Processing, and Interfaces
-Actuators and Sensor Power Systems
-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice