{"title":"Fast Response Double-Layered Graphene-Based Piezoresistive Pressure Sensor for Wearable Applications","authors":"Samira Lakouraj Mansouri;Babar Ali;Negin Faramarzi;Umar Farooq;Hossein Cheraghi Bidsorkhi;Alessandro Giuseppe D'Aloia;Alessio Tamburano;Maria Sabrina Sarto","doi":"10.1109/JSEN.2025.3577321","DOIUrl":null,"url":null,"abstract":"Recently, flexible wearable pressure sensors have garnered significant attention due to their potential in various applications. However, achieving low cost while maintaining a balance between a wide functional range, high sensitivity, fast response, and recovery times remains a significant challenge. Current research primarily emphasizes enhancing the sensitivity of these sensors, often at the expense of a broad pressure range. We present new flexible graphene-based double-layered pressure sensors characterized by a high sensitivity of 0.3 <inline-formula> <tex-math>${\\mathrm {kPa}}^{-{1}}$ </tex-math></inline-formula> across a broad working range, together with response and recovery times of 2 and 4 ms, respectively. The sensors are fabricated by casting solutions of polyvinylidene fluoride (PVDF) and graphene nanoplatelets (GNPs) onto commercial fabrics. The coated felts are then attached facing each other on their coated sides, with two electrical contacts established at opposite ends. The produced sensors undergo morphological, mechanical, and electrical characterization, and their sensing properties are assessed through electromechanical tests. They exhibit linear sensitivity, and the medium-sized specimen with the higher GNP concentration shows a 30% difference in relative resistance variation when subjected to the pressure of 160 kPa. Moreover, the produced sensors exhibit suitable stability and consistent sensing capabilities over 1000 cycles under loading-unloading test from 0 to 200 kPa. The sensors are integrated into a shoe for plantar motion monitoring and a chest belt for breathing detection. They enable accurate real-time differentiation of various breathing patterns and plantar motion, serving as a noninvasive, real-time method for detecting and monitoring medical conditions and injuries. Overall, this study presents a promising approach for developing flexible wearable sensors.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28054-28064"},"PeriodicalIF":4.3000,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11033685","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/11033685/","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}
引用次数: 0
Abstract
Recently, flexible wearable pressure sensors have garnered significant attention due to their potential in various applications. However, achieving low cost while maintaining a balance between a wide functional range, high sensitivity, fast response, and recovery times remains a significant challenge. Current research primarily emphasizes enhancing the sensitivity of these sensors, often at the expense of a broad pressure range. We present new flexible graphene-based double-layered pressure sensors characterized by a high sensitivity of 0.3 ${\mathrm {kPa}}^{-{1}}$ across a broad working range, together with response and recovery times of 2 and 4 ms, respectively. The sensors are fabricated by casting solutions of polyvinylidene fluoride (PVDF) and graphene nanoplatelets (GNPs) onto commercial fabrics. The coated felts are then attached facing each other on their coated sides, with two electrical contacts established at opposite ends. The produced sensors undergo morphological, mechanical, and electrical characterization, and their sensing properties are assessed through electromechanical tests. They exhibit linear sensitivity, and the medium-sized specimen with the higher GNP concentration shows a 30% difference in relative resistance variation when subjected to the pressure of 160 kPa. Moreover, the produced sensors exhibit suitable stability and consistent sensing capabilities over 1000 cycles under loading-unloading test from 0 to 200 kPa. The sensors are integrated into a shoe for plantar motion monitoring and a chest belt for breathing detection. They enable accurate real-time differentiation of various breathing patterns and plantar motion, serving as a noninvasive, real-time method for detecting and monitoring medical conditions and injuries. Overall, this study presents a promising approach for developing flexible wearable sensors.
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