Abstract：
Flexible strain sensors have been widely researched in fields such as smart wearables, human health monitoring, and biomedical applications. However, achieving a wide sensing range and high sensitivity of flexible strain sensors simultaneously remains a challenge, limiting their further applications. To address these issues, a cross-scale combinatorial bionic hierarchical design featuring microscale morphology combined with a macroscale base to balance the sensing range and sensitivity is presented. Inspired by the combination of serpentine and butterfly wing structures, this study employs three-dimensional printing, prestretching, and mold transfer processes to construct a combinatorial bionic hierarchical flexible strain sensor (CBH-sensor) with serpentine-shaped inverted-V-groove/wrinkling-cracking structures. The CBH-sensor has a high wide sensing range of 150% and high sensitivity with a gauge factor of up to 2416.67. In addition, it demonstrates the application of the CBH-sensor array in sign language gesture recognition, successfully identifying nine different sign language gestures with an impressive accuracy of 100% with the assistance of machine learning. The CBH-sensor exhibits considerable promise for use in enabling unobstructed communication between individuals who use sign language and those who do not. Furthermore, it has wide-ranging possibilities for use in the field of gesture-driven interactions in human-computer interfaces.
摘要：
柔性应变传感器在智能可穿戴设备等领域得到了广泛的研究,人类健康监测,和生物医学应用。然而,同时实现柔性应变传感器的宽传感范围和高灵敏度仍然是一个挑战，限制其进一步应用。为了解决这些问题,提出了一种跨尺度组合仿生分层设计，其特征是微尺度形态与宏观尺度基础相结合，以平衡传感范围和灵敏度。受蛇形和蝴蝶翅膀结构组合的启发，这项研究采用了三维打印，预拉伸,和模具转移过程，以构造具有蛇形倒V形槽/起皱开裂结构的组合仿生分层柔性应变传感器（CBH传感器）。CBH传感器具有150％的高宽传感范围和高灵敏度，仪表系数高达2416.67。此外,它展示了CBH传感器阵列在手语手势识别中的应用，在机器学习的帮助下，成功识别九种不同的手语手势，准确率达到了令人印象深刻的100%。CBH传感器在使用手语的个人和不使用手语的个人之间实现无障碍通信方面表现出相当大的前景。此外，它在人机界面中的手势驱动交互领域中具有广泛的使用可能性。
