Modeling Fabric Movement for Future E-Textile Sensors
Modeling Fabric Movement for Future E-Textile Sensors
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DOI：
10.3390/s20133735
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发表时间：
2020-07
期刊：
影响因子：
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通讯作者：
R. Ketola;Vigyanshu Mishra;A. Kiourti
中科院分区：
文献类型：
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作者：
R. Ketola;Vigyanshu Mishra;A. Kiourti
嵌入服装中的电子纺织品传感器的研究通常在静态和受控的体模模型上进行，这些模型不能反映可穿戴设备的动态特性。相反，我们的目标是了解电子纺织品传感器在现实世界中会经历的噪声。三种类型的袖子，由宽松，紧张，有弹性的织物，被施加到一个幻影臂，相应的织物运动进行了测量，在三维使用物理标记和图像处理软件。我们的研究结果表明，弹性织物允许最一致和可预测的衣服运动（平均位移高达−2.3 ± 0.1 cm），其次是紧身织物（高达−4.7 ± 0.2 cm）和宽松织物（高达−3.6 ± 1.0 cm）。此外，结果表明，较高弹性（平均位移高达−2.3 ± 0.1 cm）的弹性织物的性能优于较低弹性（平均位移高达−3.8 ± 0.3 cm）的弹性织物。对于一个依赖可穿戴环来监测关节屈曲的电子纺织传感器的案例研究，我们的建模表明，对于弹性更高的弹性织物，误差高达65.7°。这项研究的结果可以（a）帮助量化“野外”运行的电子纺织传感器的误差，（B）为有关所用服装材料的最佳类型的决策提供信息，以及（c）最终为各种电子纺织传感应用的噪声校准研究提供支持。
Studies with e-textile sensors embedded in garments are typically performed on static and controlled phantom models that do not reflect the dynamic nature of wearables. Instead, our objective was to understand the noise e-textile sensors would experience during real-world scenarios. Three types of sleeves, made of loose, tight, and stretchy fabrics, were applied to a phantom arm, and the corresponding fabric movement was measured in three dimensions using physical markers and image-processing software. Our results showed that the stretchy fabrics allowed for the most consistent and predictable clothing-movement (average displacement of up to −2.3 ± 0.1 cm), followed by tight fabrics (up to −4.7 ± 0.2 cm), and loose fabrics (up to −3.6 ± 1.0 cm). In addition, the results demonstrated better performance of higher elasticity (average displacement of up to −2.3 ± 0.1 cm) over lower elasticity (average displacement of up to −3.8 ± 0.3 cm) stretchy fabrics. For a case study with an e-textile sensor that relies on wearable loops to monitor joint flexion, our modeling indicated errors as high as 65.7° for stretchy fabric with higher elasticity. The results from this study can (a) help quantify errors of e-textile sensors operating “in-the-wild,” (b) inform decisions regarding the optimal type of clothing-material used, and (c) ultimately empower studies on noise calibration for diverse e-textile sensing applications.