Optical-Nanofiber-Enabled Gesture-Recognition Wristband for Human-Machine Interaction with the Assistance of Machine Learning
Shipeng Wang, Xiaoyu Wang, Shan Wang, Wen Yu, Longteng Yu, Lei Hou, Yao Tang, Zhang Zhang, Yao Ni, Chuan Cao, Hao Dong, Lei Zhang, Hujun Bao
- Year
- 2022
- Citations
- 3
- Access
- Open access
Abstract
The metaverse, where the virtual and real world are fused, is currently under rapid development. Immersive and vivid experience in the metaverse requires human-machine interaction devices that, unlike those currently available, are simultaneously imperceptible, convenient to use, inexpensive, and safe. In this study, we propose and realize an optical-nanofiber-based gesture-recognition wristband that can accurately recognize gestures and use them to interact with a robotic hand. Requiring only three optical-nanofiber-based pressure sensors, the wristband is simple in structure, convenient to use, and remarkably imperceptible to the user. With the assistance of a machine-learning algorithm, a maximum recognition accuracy of 94% is achieved for testers with different physiques. A robotic hand can be remotely controlled by the wristband through gestures. The wristband has broad application prospects and is a promising solution for advanced human-machine-interaction devices.
Keywords
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