Sensors (Dec 2022)

Hybrid Target Selections by ”Hand Gestures + Facial Expression” for a Rehabilitation Robot

  • Yi Han,
  • Xiangliang Zhang,
  • Ning Zhang,
  • Shuguang Meng,
  • Tao Liu,
  • Shuoyu Wang,
  • Min Pan,
  • Xiufeng Zhang,
  • Jingang Yi

DOI
https://doi.org/10.3390/s23010237
Journal volume & issue
Vol. 23, no. 1
p. 237

Abstract

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In this study we propose a “hand gesture + face expression” human machine interaction technique, and apply this technique to bedridden rehabilitation robot. “Hand gesture + Facial expression” interactive technology combines the input mode of gesture and facial expression perception. It involves seven basic facial expressions that can be used to determine a target selecting task, while hand gestures are used to control a cursor’s location. A controlled experiment was designed and conducted to evaluate the effectiveness of the proposed hybrid technology. A series of target selecting tasks with different target widths and layouts were designed to examine the recognition accuracy of hybrid control gestures. An interactive experiment applied to a rehabilitation robot is designed to verify the feasibility of this interactive technology applied to rehabilitation robots. The experimental results show that the “hand + facial expression” interactive gesture has strong robustness, which can provide a novel guideline for designing applications in VR interfaces, and it can be applied to the rehabilitation robots.

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