Investigating the effect of sensory concurrency on learning haptic spatiotemporal signals

Iain Carson, Aaron Quigley, Loraine Clarke, Uta Hinrichs

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
17 Downloads (Pure)

Abstract

A new generation of multimodal interfaces and interactions is emerging. Drawing on the principles of Sensory Substitution and Augmentation Devices (SSADs), these new interfaces offer the potential for rich, immersive human-computer interactions, but are difficult to design well, and take time to master, creating significant barriers towards wider adoption. Following a review of the literature surrounding existing SSADs, their metrics for success and their growing influence on interface design in Human Computer Interaction, we present a medium term (4-day) study comparing the effectiveness of various combinations of visual and haptic feedback (sensory concurrencies) in preparing users to perform a virtual maze navigation task using haptic feedback alone. Participants navigated 12 mazes in each of 3 separate sessions under a specific combination of visual and haptic feedback, before performing the same task using the haptic feedback alone. Visual sensory deprivation was shown to be inferior to visual & haptic concurrency in enabling haptic signal comprehension, while a new hybridized condition combining reduced visual feedback with the haptic signal was shown to be superior. Potential explanations for the effectiveness of the hybrid mechanism are explored, and the scope and implications of its generalization to new sensory interfaces is presented.
Original languageEnglish
Article number6
Pages (from-to)1-30
Number of pages30
JournalProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Volume5
Issue number1
DOIs
Publication statusPublished - 29 Mar 2021

Keywords

  • Sensory learning
  • Interface
  • Haptics
  • Augmentation
  • Vibrotactile

Fingerprint

Dive into the research topics of 'Investigating the effect of sensory concurrency on learning haptic spatiotemporal signals'. Together they form a unique fingerprint.

Cite this