Humans Can Integrate Augmented Reality Feedback in Their Sensorimotor Control of a Robotic Hand

Francesco Clemente, Strahinja Dosen, Luca Lonini, Marko Markovic, Dario Farina, Christian Cipriani

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Tactile feedback is pivotal for grasping and manipulation in humans. Providing functionally effective sensory feedback to prostheses users is an open challenge. Past paradigms were mostly based on vibro- or electrotactile stimulations. However, the tactile sensitivity on the targeted body parts (usually the forearm) is greatly less than that of the hand/fingertips, restricting the amount of information that can be provided through this channel. Visual feedback is the most investigated technique in motor learning studies, where it showed positive effects in learning both simple and complex tasks; however, it was not exploited in prosthetics due to technological limitations. Here, we investigated if visual information provided in the form of augmented reality (AR) feedback can be integrated by able-bodied participants in their sensorimotor control of a pick-and-lift task while controlling a robotic hand. For this purpose, we provided visual continuous feedback related to grip force and hand closure to the participants. Each variable was mapped to the length of one of the two ellipse axes visualized on the screen of wearable single-eye display AR glasses. We observed changes in behavior when subtle (i.e., not announced to the participants) manipulation of the AR feedback was introduced, which indicated that the participants integrated the artificial feedback within the sensorimotor control of the task. These results demonstrate that it is possible to deliver effective information through AR feedback in a compact and wearable fashion. This feedback modality may be exploited for delivering sensory feedback to amputees in a clinical scenario.

Original languageEnglish (US)
Article number7588033
Pages (from-to)583-589
Number of pages7
JournalIEEE Transactions on Human-Machine Systems
Volume47
Issue number4
DOIs
StatePublished - Aug 2017
Externally publishedYes

Keywords

  • Augmented reality (AR)
  • motor learning
  • sensorimotor control
  • sensory substitution
  • visual system
  • wearable systems

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Control and Systems Engineering
  • Signal Processing
  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

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