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Using the EEG Error Potential to Identify Interface Design Flaws

  • Jeff Escalante
  • Serena Butcher
  • Mark R. Costa
  • Leanne M. Hirshfield
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8027)

Abstract

There are a number of limitations to existing usability testing methods, including surveys, interviews, talk-alouds, and participant observations. These limitations include subject bias, poor recall, and inability to capture fleeting events, such as when a UI functions or behaves in a manner that contradicts user expectations. One possible solution to these problems is to use electrophysiological indicators to monitor user interaction with the UI. We propose using event related potentials (ERP), and the error potential (ErrP) more specifically, to capture moment-to-moment interactions that lead to violations in user expectations. An ERP is a response generated in the brain to stimuli, while the ErrP is a more specific signal shown to be elicited by subject error. In this experiment we monitored subjects using a 10-channel electroencephalogram (EEG) as they completed a range of simple web browsing tasks. However, roughly 1/3 of the time subjects were confronted with poor UI design features (e.g., broken links). We then used statistical and machine learning techniques to classify the data and found that we were able to accurately identify the presence of error potentials. Furthermore, the ErrP was present when the subjects encountered a UI design flaw, but only during the more ‘overt’ examples of our design flaws. Results support our hypothesis that ERPs and ErrPs, can be used to identify UI design flaws for a variety of systems, from web sites to video games.

Keywords

EEG usability testing error potential 

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References

  1. Coles, M., Rugg, M.D.: Event-related brain potentials: an introduction. Electrophysiology of Mind. Oxford Scholarship Online Monographs, pp. 1–27 (1996)Google Scholar
  2. Falkenstein, M., Hoormann, J., Christ, S., Hohnsbein, J.: ERP components on reaction errors and their functional significance: a tutorial. Biological Psychology (2000)Google Scholar
  3. Ferrez, P.W., Millán, J.R.: You Are Wrong! - Automatic Detection of Interaction Errors from Brain Waves. In: Proceedings of IJCAI 2005, pp. 1413–1418 (2005)Google Scholar
  4. Gehring, W.J.: The error-related negativity: Evidence for a neural mechanism for error-related processing. Dissertation Abstracts International 53(10-B), 5090–5090 (1993)Google Scholar
  5. Gehring, W.J., Goss, B., Coles, M.G.H., Meyer, D.E., Donchin, E.: A Neural System for Error Detection and Compensation. Psychological Science 4(6), 385–390 (1993)CrossRefGoogle Scholar
  6. Hirshfield, L.M., Bobko, P., Barelka, A., Hirshfield, S., Hincks, S., Gulbrunson, S., Farrington, M., Paverman, D.: Assessing Trust and Suspicion in Human-Computer Interactions Using Non-Invasive Sensors. Tech Report (2013)Google Scholar
  7. Hirshfield, L.M., Chauncey, K., Gulotta, R., Girouard, A., Solovey, E.T., Jacob, R.J.K., Sassaroli, A., Fantini, S.: Combining Electroencephalograph and Functional Near Infrared Spectroscopy to Explore Users’ Mental Workload. In: Schmorrow, D.D., Estabrooke, I.V., Grootjen, M. (eds.) FAC 2009. LNCS, vol. 5638, pp. 239–247. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  8. Miltner, W.H., Braun, C.H., Coles, M.G.: Event-related brain potentials following incorrect feedback in a time-estimation task: Evidence for a “generic” neural system for error detection. J. Cognitive Neuroscience 9(6), 788–798 (1997)CrossRefGoogle Scholar
  9. Mouraux, G.D., Iannetti: Across-trial averaging of event-related EEG responses and beyond. Magnetic Resonance Imaging 26, 1041–1054 (2008)CrossRefGoogle Scholar
  10. Nieuwenhuis, S., Ridderinkhof, R., Blom, J., Band, G.P.H., Kok, A.: Errorrelated brain potentials are differentially related to awareness of response errors: Evidence from an antisaccade task. Psychophysiology 38, 752–760 (2001)CrossRefGoogle Scholar
  11. Oliveira, F.T., McDonald, J.J., Goodman, D.: Performance monitoring in the anterior cingulate is not all error related: Expectancy deviation and the representation of action-outcome associations. Journal of Cognitive Neuroscience 19, 1994–2004 (2007)CrossRefGoogle Scholar
  12. Pailing, P.E., Segalowitz, S.J., Dywan, J., Davies, P.L.: Error negativity and reponse control. Psychophysiology 39, 198–206 (2002)CrossRefGoogle Scholar
  13. Shneiderman, B., Plaisant, C.: Designing the User Interface: Strategies for Effective Human- Computer Interaction, 4th edn. Addison-Wesley, Reading (2005)Google Scholar
  14. Sternberg, S.: High speed scanning in human memory. Science 153(736), 652–654 (1966)CrossRefGoogle Scholar
  15. Tan, D., Nijholt, A. (eds.): Brain-Computer interfaces: Applying our minds to human-computer interaction. Springer, Heidelberg (2010)Google Scholar
  16. Tatum, W.O., Husain, A.M., Benbadis, S.R.: Handbook of EEG. Interpretation. Demos Medical Publishing (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jeff Escalante
    • 1
  • Serena Butcher
    • 1
  • Mark R. Costa
    • 2
  • Leanne M. Hirshfield
    • 3
  1. 1.Hamilton CollegeSyracuse UniversityUSA
  2. 2.School of Information StudiesSyracuse UniversityUSA
  3. 3.S.I. Newhouse School of Public CommunicationsSyracuse UniversityUSA

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