Xu Ruidong, Xu Tong, She Minghua, Ji Xinran, Li Ganghua, Zhang Shijin, Zhang Xinwei, Liu Hong, Sun Bin, Shen Guozhen, Tian Mingwei
Research Center for Intelligent and Wearable Technology, College of Textiles and Clothing, State Key Laboratory of Bio-Fibers and Eco-Textiles, Health&Protective Smart Textile Research Center of Qingdao, Qingdao University, Qingdao, 266071, People's Republic of China.
Academy of Arts & Design of Qingdao University, Qingdao, 266071, People's Republic of China.
Nanomicro Lett. 2024 Dec 19;17(1):90. doi: 10.1007/s40820-024-01566-3.
Rehabilitation training is believed to be an effectual strategy that can reduce the risk of dysfunction caused by spasticity. However, achieving visualization rehabilitation training for patients remains clinically challenging. Herein, we propose visual rehabilitation training system including iontronic meta-fabrics with skin-friendly and large matrix features, as well as high-resolution image modules for distribution of human muscle tension. Attributed to the dynamic connection and dissociation of the meta-fabric, the fabric exhibits outstanding tactile sensing properties, such as wide tactile sensing range (0 ~ 300 kPa) and high-resolution tactile perception (50 Pa or 0.058%). Meanwhile, thanks to the differential capillary effect, the meta-fabric exhibits a "hitting three birds with one stone" property (dryness wearing experience, long working time and cooling sensing). Based on this, the fabrics can be integrated with garments and advanced data analysis systems to manufacture a series of large matrix structure (40 × 40, 1600 sensing units) training devices. Significantly, the tunability of piezo-ionic dynamics of the meta-fabric and the programmability of high-resolution imaging modules allow this visualization training strategy extendable to various common disease monitoring. Therefore, we believe that our study overcomes the constraint of standard spasticity rehabilitation training devices in terms of visual display and paves the way for future smart healthcare.
康复训练被认为是一种有效的策略，可以降低由痉挛引起的功能障碍风险。然而，为患者实现可视化康复训练在临床上仍然具有挑战性。在此，我们提出了一种视觉康复训练系统，包括具有亲肤和大矩阵特征的离子电子超材料，以及用于分布人体肌肉张力的高分辨率图像模块。由于超材料的动态连接和解离，该织物具有出色的触觉传感特性，如宽触觉传感范围（0 ~ 300 kPa）和高分辨率触觉感知（50 Pa或0.058%）。同时，由于差动毛细效应，该超材料具有“一石三鸟”的特性（干爽穿着体验、长工作时间和冷却传感）。基于此，这些织物可以与服装和先进的数据分析系统集成，以制造一系列大矩阵结构（40 × 40，1600个传感单元）的训练设备。值得注意的是，超材料的压电热力学动态可调性和高分辨率成像模块的可编程性使得这种可视化训练策略可扩展到各种常见疾病监测。因此，我们相信我们的研究克服了标准痉挛康复训练设备在视觉显示方面的限制，为未来的智能医疗保健铺平了道路。
