Combinatorial Bionic Hierarchical Flexible Strain Sensor for Sign Language Recognition with Machine Learning

• DOI: 10.1021/acsami.4c07868
• Publication Date: 2024-07-16T05:21:05Z
• Authors: Xuanjie Zong; Nianqiang Zhang; Jilai Wang; Hangfan Zong; Chengpeng Zhang; Guogang Xu
• Keywords: Strain (injury)

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 high sensitivity of flexible simultaneously remains challenge, limiting their further To address these issues, cross-scale combinatorial bionic hierarchical design featuring microscale morphology combined with macroscale base to balance the is presented. Inspired by combination serpentine butterfly wing structures, this study employs three-dimensional printing, prestretching, mold transfer processes construct sensor (CBH-sensor) serpentine-shaped inverted-V-groove/wrinkling-cracking structures. The CBH-sensor has 150% gauge factor up 2416.67. In addition, it demonstrates application array sign language gesture recognition, successfully identifying nine different gestures an impressive accuracy 100% assistance machine learning. exhibits considerable promise for use enabling unobstructed communication between individuals who those do not. Furthermore, wide-ranging possibilities field gesture-driven interactions human-computer interfaces.