Industrially Scalable Textile Sensing Interfaces for Extended Artificial Tactile and Human Motion Monitoring without Compromising Comfort

Abstract

Smart wearables with the capability for continuous monitoring, perceiving, and understanding human tactile and motion signals, while ensuring comfort, are highly sought after for intelligent healthcare and smart life systems. However, concurrently achieving high-performance tactile sensing, long-lasting wearing comfort, and industrialized fabrication by a low-cost strategy remains a great challenge. This is primarily due to critical research gaps in novel textile structure design for seamless integration with sensing elements. Here, an all-in-one biaxial insertion knit architecture is reported to topologically integrate sensing units within double-knit loops for the fabrication of a large-scale tactile sensing textile by using low-cost industrial manufacturing routes. High sensitivity, stability, and low hysteresis of arrayed sensing units are achieved through engineering of fractal structures of hierarchically patterned piezoresistive yarns via blistering and twisting processing. The as-prepared tactile sensing textiles show desirable sensing performance and robust mechanical property, while ensuring excellent conformability, tailorability, breathability (288 mm s–1), and moisture permeability (3591 g m–2 per day) for minimizing the effect on wearing comfort. The multifunctional applications of tactile sensing textiles are demonstrated in continuously monitoring human motions, tactile interactions with the environment, and recognizing biometric gait. Moreover, we also demonstrate that machine learning-assisted sensing textiles can accurately predict body postures, which holds great promise in advancing the development of personalized healthcare robotics, prosthetics, and intelligent interaction devices.

Publication
ACS Applied Materials & Interfaces
Pengpeng Hu
Pengpeng Hu
Assistant Professor

Pengpeng Hu is currently an Assistant Professor with the Center for Computational Science and Mathematical Modeling, Coventry University, Coventry, U.K. He was a Senior Researcher with the Department of Electronics and Informatics, Vrije Universiteit Brussel (VUB), Brussels, Belgium. In 2016, he was a Visiting Scholar with the School of Informatics, Edinburgh University, Edinburgh, U.K. In 2017, he was a Post-Doctoral Fellow with the Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, U.K. Since 2018, he has been with VUB. His current research interests include biometrics, geometric deep learning, 3-D human body reconstruction, point cloud processing, and measurement.