Using fNIRS brain sensing to evaluate information visualization interfaces

  • Evan M. Peck
  • , Beste F. Yuksel
  • , Alvitta Ottley
  • , Robert J.K. Jacob
  • , Remco Chang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

87 Scopus citations

Abstract

We show how brain sensing can lend insight to the evaluation of visual interfaces and establish a role for fNIRS in visualization. Research suggests that the evaluation of visual design benefits by going beyond performance measures or questionnaires to measurements of the user's cognitive state. Unfortunately, objectively and unobtrusively monitoring the brain is difficult. While functional near-infrared spectroscopy (fNIRS) has emerged as a practical brain sensing technology in HCI, visual tasks often rely on the brain's quick, massively parallel visual system, which may be inaccessible to this measurement. It is unknown whether fNIRS can distinguish differences in cognitive state that derive from visual design alone. In this paper, we use the classic comparison of bar graphs and pie charts to test the viability of fNIRS for measuring the impact of a visual design on the brain. Our results demonstrate that we can indeed measure this impact, and furthermore measurements indicate that there are not universal differences in bar graphs and pie charts.

Original languageEnglish
Title of host publicationCHI 2013
Subtitle of host publicationChanging Perspectives, Conference Proceedings - The 31st Annual CHI Conference on Human Factors in Computing Systems
Pages473-482
Number of pages10
DOIs
StatePublished - 2013
Event31st Annual CHI Conference on Human Factors in Computing Systems: Changing Perspectives, CHI 2013 - Paris, France
Duration: Apr 27 2013May 2 2013

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference31st Annual CHI Conference on Human Factors in Computing Systems: Changing Perspectives, CHI 2013
Country/TerritoryFrance
CityParis
Period04/27/1305/2/13

Keywords

  • BCI
  • Brain sensing
  • Evaluation
  • FNIRS
  • Visualization

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