Programmable Triboelectric Origami Sensors for Multidimensional Pressure Monitoring
Tao Liu, Rongrong Liang, Yaping Zeng, Huanjie He, Kang Yu, Mingchao Chi, Qiguan Luo, Lijun Wang, Dengjun Lu, Shuangxi Nie
- 发表年份
- 2026
- 引用次数
- 4
摘要
Sensors with multidimensional pressure sensing capabilities have attracted extensive interest for applications in wearable electronics and human-computer interaction. However, conventional film-based materials struggle to achieve directional stress perception and exhibit limited sensitivity. Inspired by origami, this work integrates self-folding with composite loading to construct programmable 3D origami sensors. The design enables flexible assembly of multichannel sensing matrices, converting single-point signals into multidimensional responses that simultaneously acquire stress intensity and directional information. Coupled with deep learning algorithms, the origami sensor achieves a recognition accuracy of 97.8%. Furthermore, structural design augments the sensor's responsive performance, with a sensitivity approximately 130 times higher than that of the substrate material, while its output power density rivals that of various advanced sensors. This study overcomes the inherent limitations of traditional films in directional stress sensing and holds profound significance for the advancement of wearable electronics and intelligent robotics.
关键词
相关论文
Artificial intelligence: a modern approach
1995
Are we ready for autonomous driving? The KITTI vision benchmark suite
Andreas Geiger, P Lenz, R. Urtasun
2012
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martı́n Abadi, Ashish Agarwal, Paul Barham 等 20 位作者
2016
Vision meets robotics: The KITTI dataset
Andreas Geiger, Philip Lenz, Christoph Stiller 等 4 位作者
2013