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i-GSI: A Novel Grasp Switching Interface Based on Eye-Tracking and Augmented Reality for Multi-Grasp Prosthetic Hands

  • Harbin Institute of Technology
  • Artificial Intelligence Laboratory (HAI)

Research output: Contribution to journalArticlepeer-review

Abstract

Controlling multi-grasp prosthetic hands remains challenging due to the lack of an intuitive and efficient interface for enabling a suitable grasping pattern. To solve this problem, we propose an eye-tracking based grasp switching interface (i-GSI) that integrates the 'GazeButton' from augmented reality (AR) to elicit the intended grasp patterns from eye movements. The i-GSI is fully implemented in HoloLens 2 (Microsoft, USA), and its user can easily switch between six grasp types with just a glance at the GazeButtons. Experiments on eight healthy subjects shows that the average switching time is nearly 0.84 s, with a success rate of 99.0% and a learning efficiency of 93.5%. Results on a congenital amputee also shows a similar outcome (switching time 0.78 s, success rate 100%). Compared with the other three traditional methods, our i-GSI achieved the best performance. The i-GSI also shows a superior adaptability to different users with various amputation levels, when combining with a simple myoelectric control (such as, two-sites proportional control).

Original languageEnglish
Pages (from-to)1619-1626
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume8
Issue number3
DOIs
StatePublished - 1 Mar 2023

Keywords

  • Eye-tracking
  • augmented reality
  • grasping
  • human-machine interface
  • prosthesis

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