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Optical-Nanofiber-Enabled Gesture-Recognition Wristband for Human-Machine Interaction with the Assistance of Machine Learning
  • +10
  • Shipeng Wang,
  • Xiaoyu Wang,
  • Shan Wang,
  • Wen Yu,
  • Longteng Yu,
  • Lei Hou,
  • Yao Tang,
  • Zhang Zhang,
  • Ni Yao,
  • Chuan Cao,
  • Hao Dong,
  • Lei Zhang,
  • Hujun Bao
Shipeng Wang
Author Profile
Xiaoyu Wang
Shan Wang
Wen Yu
Longteng Yu
Lei Hou
Yao Tang
Zhang Zhang
Ni Yao
Chuan Cao
Hao Dong
Lei Zhang

Corresponding Author:

Hujun Bao

Corresponding Author:


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.
30 Nov 2022Submitted to AISY Interactive Papers
05 Dec 2022Published in AISY Interactive Papers