Chen Liming, Lu Mingyang, Yang Haosen, Salas Avila Jorge Ricardo, Shi Bowen, Ren Lei, Wei Guowu, Liu Xuqing, Yin Wuliang
Department of Electrical and Electronic Engineering, University of Manchester, Sackville Street Building, Manchester M13 9PL, United Kingdom.
Department of Mechanical, Aerospace, and Civil Engineering, University of Manchester, Sackville Street Building, Manchester M13 9PL, United Kingdom.
ACS Nano. 2020 Jul 28;14(7):8191-8201. doi: 10.1021/acsnano.0c01643. Epub 2020 Jun 14.
Wearable sensor technologies, especially continuous monitoring of various human health conditions, are attracting increased attention. However, current rigid sensors present obvious drawbacks, like lower durability and poor comfort. Here, a strategy is proposed to efficiently yield wearable sensors using cotton fabric as an essential component, and conductive materials conformally coat onto the cotton fibers, leading to a highly electrically conductive interconnecting network. To improve the conductivity and durability of conductive coatings, a topographical modification approach is developed with genus-3 and genus-5 structures, and topological genus structures enable cage metallic seeds on the surface of substrates. A textile-based capacitive sensor with flexible, comfortable, and durable properties has been demonstrated. High sensitivity and convenience of signal collection have been achieved by the excellent electrical conductivity of this sensor. Based on results of deep investigation on capacitance, effects of distance and angles between two conductive fabrics contribute to the capacitive sensitivity. In addition, the textile-based capacitive sensor has successfully been used for real-time monitoring human breathing, speaking, blinking, and joint motions during physical rehabilitation exercises.
可穿戴传感器技术，尤其是对各种人体健康状况的连续监测，正吸引着越来越多的关注。然而，目前的刚性传感器存在明显的缺点，如耐久性较低和舒适性差。在此，提出了一种策略，以棉织物为主要成分高效制备可穿戴传感器，导电材料保形地包覆在棉纤维上，形成高度导电的互连网络。为了提高导电涂层的导电性和耐久性，开发了一种具有亏格3和亏格5结构的形貌改性方法，拓扑亏格结构使基底表面形成笼状金属籽晶。已经展示了一种具有柔性、舒适性和耐久性的基于纺织品的电容式传感器。该传感器优异的导电性实现了高灵敏度和信号采集的便利性。基于对电容的深入研究结果，两块导电织物之间的距离和角度影响电容灵敏度。此外，基于纺织品的电容式传感器已成功用于实时监测人体呼吸、说话、眨眼以及物理康复锻炼期间的关节运动。
