Low-Cost Magnetorheological Elastomer-Based Capacitive Flexible Sensor Arrays for Human--Machine Interaction and Wearable Sensing

IF 4.5 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
IEEE Sensors Journal Pub Date : 2026-10-15 Epub Date: 2026-09-09 DOI:10.1109/JSEN.2026.3728160
Benyuan Fu;Hao Wang;Lin Jia;Xinxin Yuan;Zhiyuan Zou;Zhengqiu Xie
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Abstract

Flexible tactile sensor arrays are widely used in human–machine interaction (HMI) and wearable sensing; however, achieving both high sensitivity and a wide detection range while maintaining a simple fabrication process remains challenging. This work presents a cost-effective flexible piezocapacitive sensor array based on a bilayer magnetorheological elastomer (MRE) dielectric architecture. The device consists of a carbonyl nickel-filled silicone rubber layer and a polyvinyl alcohol hydrogel (PVA-H) layer, forming a mechanically heterogeneous interface that enhances pressure-induced capacitance modulation through improved mechanical–dielectric coupling. In addition, magnetically induced particle structuring within the MRE promotes interfacial polarization and contributes to the dielectric response under compression. Compared with conventional single-layer capacitive sensors, the proposed architecture improves sensing performance without requiring complex microstructuring processes. The fabricated $6\times 6$ sensor array demonstrates stable operation, achieving sensitivities of 0.713 kPa -1 in the low-pressure range (0–60 kPa) and 2.483 kPa -1 in the high-pressure range (60–100 kPa), together with response and recovery times of approximately 120 ms. The device also exhibits good repeatability and consistency among sensing units. Practical demonstrations, including spatial pressure mapping, motion trajectory recognition, and human activity monitoring, verify its capability for real-time tactile sensing. This work provides a simple and scalable MRE-based bilayer dielectric design strategy for flexible capacitive sensors and shows potential for applications in wearable electronics, electronic skin, and intelligent human–machine interfaces.
用于人机交互和可穿戴传感的低成本磁流变弹性体电容式柔性传感器阵列
柔性触觉传感器阵列广泛应用于人机交互(HMI)和可穿戴传感领域;然而,在保持简单的制造工艺的同时实现高灵敏度和宽检测范围仍然具有挑战性。本文提出了一种基于双层磁流变弹性体(MRE)介电结构的高性价比柔性压电容传感器阵列。该装置由羰基镍填充硅橡胶层和聚乙烯醇水凝胶(PVA-H)层组成,形成机械非均质界面,通过改进机械-介电耦合增强压力感应电容调制。此外,磁致粒子结构在MRE中促进了界面极化,并有助于压缩下的介电响应。与传统的单层电容式传感器相比,该结构在不需要复杂微结构工艺的情况下提高了传感性能。制备的6 × 6传感器阵列工作稳定,在低压范围(0-60 kPa)和高压范围(60-100 kPa)下的灵敏度分别为0.713 kPa -1和2.483 kPa -1,响应和恢复时间约为120 ms。该装置还具有良好的重复性和传感单元之间的一致性。实际演示,包括空间压力映射、运动轨迹识别和人类活动监测,验证了其实时触觉传感的能力。这项工作为柔性电容传感器提供了一种简单且可扩展的基于mre的双层介电设计策略,并显示了在可穿戴电子产品,电子皮肤和智能人机界面中的应用潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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