Programmable and Scalable Embroidery Textile Resistive Pressure Sensors for Integrated Multifunctional Smart Wearable Systems

IF 17.2 1区 工程技术 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Yiduo Yang, Yu Chen, Yang Liu, Rong Yin
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Abstract

Conformable and breathable textile structures are ideal for flexible wearable pressure sensors, yet challenges remain in scalable fabrication, easy integration, and programmability. This study presents a cost-effective and customizable method to create fully textile-based pressure sensors using machine embroidery, enabling seamless integration into smart wearable systems. Two sensing configurations were developed: a single-layer satin block embroidered with conductive yarn, which exhibited high piezoresistivity, fast response (35 ms), quick recovery (16 ms), and robust durability over 5000 press-and-release cycles, proven effective for monitoring activities such as plantar pressure and muscle contraction, and making it suitable for personalized health and fitness applications. The second configuration, a double-layer embroidery sensor with a conductive path and two parallel spacers anchored beneath a satin block, allows for array integration with minimal wiring, demonstrated by a 3 × 3 sensing array that, with the help of a convolutional neural network (CNN) machine learning model, accurately recognized handwritten numbers (0–9) with a 98.5% accuracy, showing its potential for user authentication and secure passcode entry. These findings underscore the potential of machine embroidery for developing scalable, integrated, and high-performance intelligent textile systems, paving the way for wearable technologies that are customizable, comfortable, and aesthetically appealing for a wide range of applications.

Graphical Abstract

用于集成多功能智能可穿戴系统的可编程和可扩展刺绣纺织品电阻压力传感器
舒适透气的纺织结构是柔性可穿戴压力传感器的理想选择,但在可扩展制造、易于集成和可编程性方面仍然存在挑战。这项研究提出了一种成本效益高、可定制的方法,利用机器刺绣来制造完全基于纺织品的压力传感器,使其能够无缝集成到智能可穿戴系统中。开发了两种传感配置:一种是绣有导电纱的单层缎面块,具有高压阻性、快速响应(35毫秒)、快速恢复(16毫秒)和超过5000次按压和释放周期的耐用性,被证明对监测足底压力和肌肉收缩等活动有效,适合个性化健康和健身应用。第二种配置是双层刺绣传感器,带有导电路径和固定在缎面块下方的两个平行垫片,允许以最少的布线进行阵列集成,3 × 3传感阵列在卷积神经网络(CNN)机器学习模型的帮助下,以98.5%的准确率准确识别手写数字(0-9),显示其在用户身份验证和安全密码输入方面的潜力。这些发现强调了机器刺绣在开发可扩展、集成和高性能智能纺织系统方面的潜力,为可定制、舒适和美观的可穿戴技术铺平了道路,适用于广泛的应用。图形抽象
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来源期刊
CiteScore
18.70
自引率
11.20%
发文量
109
期刊介绍: Advanced Fiber Materials is a hybrid, peer-reviewed, international and interdisciplinary research journal which aims to publish the most important papers in fibers and fiber-related devices as well as their applications.Indexed by SCIE, EI, Scopus et al. Publishing on fiber or fiber-related materials, technology, engineering and application.
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