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Learning and Identifying Haptic Icons Under Workload

Chan, Andrew and MacLean, Karon and McGrenere, Joanna

 

Info
ID: CHA2005:01 2005
File: CHA2005_01_-_Learning_Hapticons_Workload.pdf
DOI   
Note: PDF Articles only available for those with access to the TU/e ID S-Drive.
Keywords

Keywords:

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. Our testbed
will be a novel urgency-based turn-taking protocol for
remote collaboration, and our setup uses inexpensive
off-the-shelf technology. We describe two studies
designed to (a) perceptually optimize a set of
vibrotactile "icons" for our protocol and (b) evaluate
users' ability to identify them in the presence of
varying degrees of workload.

We found that 7 icons learned in approximately 3
minutes were each typically identified within 2.5 s and
at 95% accuracy in the absence of workload. With
added visual and auditory distractor tasks, the time
required to detect a change in haptic icon increased
from 1.9 s to an average of 4.3 s. We further provide
initial parameters to help designers intelligently
balance the need to support communication while
minimizing disruption.

Details
address Pisa, Italy organization
booktitle Proceedings of WorldHaptics 2005 pages pp. 432-439
chapter publisher
crossref school
edition series
editor type
howpublished volume
institution year 2005
journal mycomments*
key source*
language file* CHA2005_01_-_Learning_Hapticons_Workload.pdf:CHA2005_01_-_Learning_Hapticons_Workload.pdf:PDF
month isbn*
note DOI http://doi.ieeecomputersociety.org/10.1109/WHC.2005.86
number annote*