A User Study of Visualization Effectiveness Using EEG and Cognitive Load

E. W. Anderson, K. C. Potter, L. E. Matzen, J. F. Shepherd, G. A. Preston, C. T. Silva

Research output: Contribution to journalArticlepeer-review

154 Scopus citations

Abstract

Effectively evaluating visualization techniques is a difficult task often assessed through feedback from user studies and expert evaluations. This work presents an alternative approach to visualization evaluation in which brain activity is passively recorded using electroencephalography (EEG). These measurements are used to compare different visualization techniques in terms of the burden they place on a viewer's cognitive resources. In this paper, EEG signals and response times are recorded while users interpret different representations of data distributions. This information is processed to provide insight into the cognitive load imposed on the viewer. This paper describes the design of the user study performed, the extraction of cognitive load measures from EEG data, and how those measures are used to quantitatively evaluate the effectiveness of visualizations. © 2011 The Author(s).
Original languageEnglish (US)
Pages (from-to)791-800
Number of pages10
JournalComputer Graphics Forum
Volume30
Issue number3
DOIs
StatePublished - Jun 28 2011
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUS-C1-016-04
Acknowledgements: The authors would like to thank the anonymous reviewers for their insightful comments. We also thank Dr. Laura McNamara for discussions on experimental design, and Dr. Joel Daniels II for his help and advice. This work was supported in part by grants from the National Science Foundation (IIS-0905385, CNS-0855167, IIS-0844546, ATM-0835821, CNS-0751152, OCE-0424602, CNS-0514485, IIS-0513692, CNS-0524096, CCF-0401498, OISE-0405402, CCF-0528201, CNS-0551724, CNS-0615194), Award No. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST), the Department of Energy, and IBM Faculty Awards.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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