Learning and Identifying Haptic Icons under Workload

  • Authors:
  • Andrew Chan;Karon MacLean;Joanna McGrenere

  • Affiliations:
  • University of British Columbia;University of British Columbia;University of British Columbia

  • Venue:
  • WHC '05 Proceedings of the First Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems
  • Year:
  • 2005

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Abstract

This work addresses the use of vibrotactile haptic feedback to transmit background information with variable intrusiveness, when recipients are engrossed in a primary visual and/or auditory task. We describe two studies designed to (a) perceptually optimize a set of vibrotactile "icons" and (b) evaluate users' ability to identify them in the presence of varying degrees of workload. Seven icons learned in approximately 3 minutes were each typically identified within 2.5 s and at 95% accuracy in the absence of workload. An extended version of this paper can be found as a technical report at http://www.cs.ubc.ca/labs/spin/.