针织结构对机电指标的影响及其与针织应变传感器关节角度估计误差的相关性
Knit-Structure Effects on Electromechanical Metrics and Their Correlation with Joint-Angle Estimation Error in Knitted Strain Sensors
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中文总结 AI 辅助
本研究探讨针织结构对机电指标的影响，发现应变系数和基线电阻可预测关节角度估计误差，支持用单轴拉伸测试筛选弱设计。
中文摘要 AI 辅助
针织电阻式应变传感器在运动和康复领域的关节运动感知中展现出巨大潜力，但传感器设计与实际性能之间的联系仍不明确。我们研究了针织结构和机器设置（如针距）如何塑造机电性能，以及哪些指标能预测弯曲过程中的传感性能。我们制作了涵盖七种常见针织结构、两种针距的传感器，在单轴循环拉伸下进行表征，并在模拟关节弯曲的装置上进行了评估。使用机器学习模型评估关节角度估计，并分析了与机电指标的相关性。实验结果表明，在六种常见指标中，应变系数和基线电阻主要由针织结构决定，而工作范围、线性范围、迟滞和循环稳定性在不同设计间变化不大。应变系数与关节角度估计误差呈负相关，基线电阻呈正相关，主要出现在低灵敏度设计中，而其他指标的预测价值较弱或没有。这些结果支持使用单轴拉伸测试筛选弱设计，同时强调了需要关节相关评估和应用特定指标来识别最佳性能者。
英文摘要
Knitted resistive strain sensors show strong promise for joint motion sensing in sports and rehabilitation, but the linkage between sensor design and in situ performance remains unclear. We investigate how knit structure and machine settings (e.g., stitch size) shape electromechanical properties and which metrics predict sensing performance during bending. Sensors spanning seven common knit structures at two stitch sizes were fabricated, characterized under uniaxial cyclic tension, and evaluated on a joint emulating bending rig. Joint-angle estimation was assessed with machine learning models, and correlations with electromechanical metrics were analyzed. Experimental results show that, among six common metrics, gauge factor and baseline resistance are largely set by knit structure, while working range, linear range, hysteresis, and cyclic stability vary only modestly across designs. Gauge factor correlates negatively and baseline resistance positively with joint-angle estimation error, mainly in lower-sensitivity designs, whereas the other metrics have weak or no predictive value. These results support using uniaxial tensile tests to screen out weak designs, while underscoring the need for joint-relevant evaluation and application-specific metrics to identify top performers.
发表机构
- Aalto University（阿尔托大学）
- Loughborough University（拉夫堡大学）
机构由 AI 辅助整理，请以论文原文为准。
