Key Laboratory of Eco-textiles of Ministry of Education, Jiangnan University, Wuxi 214122, China.
Centre for Computer Science and Mathematical Modelling, Coventry University, Coventry CV1 5FB, U.K.
ACS Appl Mater Interfaces. 2024 Apr 3;16(13):16788-16799. doi: 10.1021/acsami.4c00423. Epub 2024 Mar 23.
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), and moisture permeability (3591 g m 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.
智能可穿戴设备具有连续监测、感知和理解人体触觉和运动信号的能力,同时确保舒适性,因此非常适合智能医疗保健和智能生活系统。然而,通过低成本策略同时实现高性能触觉传感、持久的佩戴舒适性和工业化制造仍然是一个巨大的挑战。这主要是由于新型纺织结构设计用于与传感元件无缝集成的关键研究空白。在这里,报告了一种整体的双向插入针织结构,通过泡胀和扭曲处理对分层图案压阻纱线的分形结构进行工程设计,从而在双针织圈中拓扑集成传感单元,以制造大规模的触觉传感纺织品。通过这种方法,阵列式传感单元实现了高灵敏度、稳定性和低滞后性。所制备的触觉传感纺织品具有良好的传感性能和稳健的机械性能,同时确保了出色的贴合性、可定制性、透气性(288mm/s)和透湿性(3591g/m/天),以最大限度地减少对佩戴舒适性的影响。触觉传感纺织品的多功能应用在连续监测人体运动、与环境的触觉交互以及识别生物步态方面得到了展示。此外,我们还证明了基于机器学习的传感纺织品可以准确预测身体姿势,这在推进个性化医疗机器人、义肢和智能交互设备的发展方面具有很大的潜力。