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    A User Study of Visualization Effectiveness Using EEG and Cognitive Load

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    Type
    Article
    Authors
    Anderson, E. W.
    Potter, K. C.
    Matzen, L. E.
    Shepherd, J. F.
    Preston, G. A.
    Silva, C. T.
    KAUST Grant Number
    KUS-C1-016-04
    Date
    2011-06-28
    Online Publication Date
    2011-06-28
    Print Publication Date
    2011-06
    Permanent link to this record
    http://hdl.handle.net/10754/597433
    
    Metadata
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    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).
    Citation
    Anderson EW, Potter KC, Matzen LE, Shepherd JF, Preston GA, et al. (2011) A User Study of Visualization Effectiveness Using EEG and Cognitive Load. Computer Graphics Forum 30: 791–800. Available: http://dx.doi.org/10.1111/j.1467-8659.2011.01928.x.
    Sponsors
    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.
    Publisher
    Wiley
    Journal
    Computer Graphics Forum
    DOI
    10.1111/j.1467-8659.2011.01928.x
    ae974a485f413a2113503eed53cd6c53
    10.1111/j.1467-8659.2011.01928.x
    Scopus Count
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