数字创新中心

Center for Digital Innovation

LayTex: A Design Tool for Generating Customized Textile Sensor Layouts in Wearable Computing

Yueyao Zhang, Nianchong Qu, Runhua Zhang, Ye Tao, Guanyun Wang, Qi Wang

UbiComp/ISWC ’23 Adjunct

摘要/Abstract

智能织物传感器在可穿戴计算领域的人体运动监测中受到越来越多的关注。以往的研究表明,织物传感器的布局对可穿戴原型的有效性和性能具有重要影响。然而,采用定量方法确定织物传感器布局仍然是一个复杂且耗时的问题,因为这涉及到传感器的数量、位置以及方向的确定,当前尚无专门解决此问题的高效数字平台或工具。本文介绍了一种名为LayTex的数字工具,该工具能够为个性化场景生成布局方案,旨在帮助设计师和研究人员高效构建原型。与设计师在脊柱侧弯智能服装方面的初步评估表明,LayTex具有降低门槛并简化织物原型构建过程的巨大潜力。

Smart textile sensors have attracted increasing interest in the domain of wearable computing for human motion monitoring. Previous studies have shown that textile sensor layout has a major impact on the effectiveness and performance of wearable prototypes. However, it is still a trick and time-consuming issue to determine textile sensor layout in a quantitative approach as it involves figuring out the number, placement, and even orientations of sensors, yet there is no streamlined digital platform or tool specifically addressing this issue. In this paper, we introduce LayTex, a digital tool capable of generating layout proposals for personalized scenarios, which aims at facilitating designers and researchers to construct prototypes efficiently. The preliminary evaluation with designers on smart garments for scoliosis indicates that LayTex has great potential to lower the barriers and simplify the process of textile prototype construction.

相关信息/Info

作者/Authors

链接/Link

Yueyao Zhang, Nianchong Qu, Runhua Zhang, Ye Tao, Guanyun Wang, Qi Wang

https://dl.acm.org/doi/10.1145/3594739.3610692

图片/Figures