Effects of multimodal feedback on the performance of older adults with normal and impaired vision

Julie A. Jacko, Ingrid U. Scott, François Sainfort, Kevin P. Moloney, Thitima Kongnakorn, Brynley S. Zorich, V. Kathlene Emery

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

The augmentation of computer technologies with multimodal interfaces has great potential for improving interaction with these technologies via the use of different sensory feedback. This may be of particular importance for individuals from divergent user populations, who have varying interaction needs and abilities. This study examines the effects of a multimodal interface, utilizing auditory, haptic, and visual feedback, on the performance of elderly users with varying levels of visual abilities. Older adults who possess normal vision (n=29) and those who have been diagnosed with age-related macular degeneration (AMD) (n=30), with different levels of visual acuity, were involved in the study. Participants were asked to complete a series of 'drag-and-drop' tasks under varying forms of feedback. User performance was assessed with the measure of final target highlight time. The findings suggest that the addition of other feedback modalities, to the traditionally used visual feedback form, can enhance the performance of users, particularly those with visual impairments.

Original languageEnglish (US)
Pages (from-to)3-22
Number of pages20
JournalLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume2615
DOIs
StatePublished - 2003

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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