Fast Response Double-Layered Graphene-Based Piezoresistive Pressure Sensor for Wearable Applications

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Samira Lakouraj Mansouri;Babar Ali;Negin Faramarzi;Umar Farooq;Hossein Cheraghi Bidsorkhi;Alessandro Giuseppe D'Aloia;Alessio Tamburano;Maria Sabrina Sarto
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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.
用于可穿戴应用的快速响应双层石墨烯压阻压力传感器
近年来,柔性可穿戴压力传感器因其在各种应用领域的潜力而备受关注。然而,在实现低成本的同时保持宽功能范围、高灵敏度、快速响应和恢复时间之间的平衡仍然是一个重大挑战。目前的研究主要强调提高这些传感器的灵敏度,往往以牺牲较宽的压力范围为代价。我们提出了一种新的柔性石墨烯双层压力传感器,其特点是在宽工作范围内具有0.3 ${\ mathm {kPa}}^{-{1}}$的高灵敏度,响应和恢复时间分别为2 ms和4 ms。这种传感器是通过将聚偏氟乙烯(PVDF)和石墨烯纳米片(GNPs)溶液浇铸到商用织物上制成的。然后,涂覆的毛毡在其涂覆的两侧相互连接,在两端建立两个电触点。所生产的传感器经过形态学、力学和电学表征,并通过机电测试评估其传感性能。它们表现出线性敏感性,当施加160 kPa压力时,GNP浓度较高的中型试件的相对阻力变化差异为30%。此外,所生产的传感器在0至200 kPa的加载-卸载测试中,在1000次循环中表现出合适的稳定性和一致的传感能力。传感器被集成到鞋子中用于足底运动监测和胸带中用于呼吸检测。它们能够准确地实时区分各种呼吸模式和足底运动,作为一种非侵入性的实时方法,用于检测和监测医疗状况和损伤。总的来说,这项研究为开发柔性可穿戴传感器提供了一种很有前途的方法。
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
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
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