Path-Following Guidance Using Phantom Sensation Based Vibrotactile CuAround the Wrist

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Vibrotactile feedback systems for supporting human motion have been widely researched, mainly owing to the low price and reduced size of vibration motors, which allow trainees to actively move while using them. Most existing vibrotactile feedback systems focus on providing information about the human's joint angles, making it necessary to understand multiple simultaneous stimuli to guide the trajectory of a limb. Instead, in the present study, we focus on guiding the motion of the hand by following an endpoint approach and propose a vibrotactile feedback paradigm to convey a direction around the wrist and guide the user's wrist around points in a two-dimensional Cartesian space. In the path-following task, vibrotactile cues are provided as direction information to modify the wrist's path only when the wrist's position deviates significantly from the desired path. The experiment was designed based on the motor learning process to observe the evolution of performance during training. We found that the root mean squared error of participants decreased by 49.3% when provided with vibrotactile feedback. This effect was almost constant throughout training. Additionally, most participants could reproduce the desired path after removing the provided feedback immediately after training. We believe the proposed system can be applied to enhance the process of learning tasks that require hand guidance, such as learning of Japanese calligraphy or upper limb rehabilitation.

Original languageEnglish
Pages (from-to)2485-2492
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume3
Issue number3
DOIs
Publication statusPublished - 2018 Jul

Keywords

  • Haptics and haptic interfaces
  • physically assistive devices
  • wearable robots

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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