ABSTRACT
Measuring brain activity with electroencephalography (EEG) is mature enough to assess mental states. Combined with existing methods, such tool can be used to strengthen the understanding of user experience. We contribute a set of methods to estimate continuously the user's mental workload, attention and recognition of interaction errors during different interaction tasks. We validate these measures on a controlled virtual environment and show how they can be used to compare different interaction techniques or devices, by comparing here a keyboard and a touch-based interface. Thanks to such a framework, EEG becomes a promising method to improve the overall usability of complex computer systems.
Supplemental Material
- Chris Berka and DJ Levendowski. 2007. EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks. Aviat Space Environ Med. 78, 5 Suppl (May 2007), B231--44.Google Scholar
- Benjamin Blankertz, Michael Tangermann, Carmen Vidaurre, Siamac Fazli, Claudia Sannelli, Stefan Haufe, Cecilia Maeder, Lenny Ramsey, Irene Sturm, Gabriel Curio, and Klaus-Robert Müller. 2010. The Berlin Brain-Computer Interface: Non-Medical Uses of BCI Technology. Front Neurosci 4 (Jan. 2010), 198.Google Scholar
- Christopher G. Burns and Stephen H. Fairclough. 2015. Use of auditory event-related potentials to measure immersion during a computer game. International Journal of Human-Computer Studies 73 (2015), 107--114.Google ScholarCross Ref
- Ula Cartwright-Finch and Nilli Lavie. 2007. The role of perceptual load in inattentional blindness. Cognition 102, 3 (2007), 321--340.Google ScholarCross Ref
- J T Coull. 1998. Neural correlates of attention and arousal: insights from electrophysiology, functional neuroimaging and psychopharmacology. Progress in neurobiology 55, 4 (July 1998), 343--61.Google Scholar
- Edward Cutrell and Desney Tan. 2008. BCI for passive input in HCI. CHI '08 Workshops (2008), 1--3.Google Scholar
- Sebastian Deterding, Dan Dixon, Rilla Khaled, and Lennart Nacke. 2011. From game design elements to gamefulness. In MindTrek '11. 9. Google ScholarDigital Library
- Stephen H. Fairclough. 2009. Fundamentals of physiological computing. Interacting with Comp. 21, 1--2 (Jan. 2009), 133--145. Google ScholarDigital Library
- Pierre W Ferrez and Jose Del R Millan. 2008. Error-related EEG potentials generated during simulated brain-computer interaction. IEEE Trans. Biomed. Eng. 55, 3 (March 2008), 923--9.Google ScholarCross Ref
- David R. Flatla, Carl Gutwin, Lennart E. Nacke, Scott Bateman, and Regan L. Mandryk. 2011. Calibration games: making calibration tasks enjoyable by adding motivating game elements. UIST '11 (2011), 403--412. Google ScholarDigital Library
- Jérémy Frey, Christian Mühl, Fabien Lotte, and Martin Hachet. 2014. Review of the use of electroencephalography as an evaluation method for human-computer interaction. In PhyCS '14.Google Scholar
- David Grimes, DS Tan, and SE Hudson. 2008. Feasibility and pragmatics of classifying working memory load with an electroencephalograph. CHI '08 (2008), 835. Google ScholarDigital Library
- F.E. Grubbs. 1969. Procedures for Detecting Outlying Observations in Samples. Technometrics 11, 1 (1969), 1--21.Google ScholarCross Ref
- SG Hart and LE Staveland. 1988. Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. In Human mental workload.Google Scholar
- Leanne M. Hirshfield, Erin Treacy Solovey, Audrey Girouard, James Kebinger, Robert J.K. Jacob, Angelo Sassaroli, and Sergio Fantini. 2009. Brain measurement for usability testing and adaptive interfaces. In CHI '09. ACM Press, NY, NY, USA, 2185. Google ScholarDigital Library
- Ulrich Hoffmann, JM Vesin, and Touradj Ebrahimi. 2006. Spatial filters for the classification of event-related potentials. In ESANN '06.Google Scholar
- J. Matias Kivikangas, Inger Ekman, Guillaume Chanel, Simo Järvelä, Ben Cowley, Pentti Henttonen, and Niklas Ravaja. 2010. Review on psychophysiological methods in game research. Proc. of 1st Nordic DiGRA (2010).Google Scholar
- Olivier Ledoit and Michael Wolf. 2004. A well-conditioned estimator for large-dimensional covariance matrices. J Multivar Anal (Feb. 2004). Google ScholarDigital Library
- A. John Maule and Anne C Edland. 1997. The effects of time pressure on human judgment and decision making. In Decision making: Cognitive models and Explanations.Google Scholar
- Ranjana K Mehta and Raja Parasuraman. 2013. Neuroergonomics: a review of applications to physical and cognitive work. Frontiers in human neuroscience 7, December (Jan. 2013), 889.Google Scholar
- Ernst Niedermeyer and FH Lopes da Silva. 2005. Electroencephalography: basic principles, clinical applications, and related fields. LWW.Google Scholar
- S Nieuwenhuis, K R Ridderinkhof, J Blom, G P Band, and A Kok. 2001. Error-related brain potentials are differentially related to awareness of response errors: evidence from an antisaccade task. Psychophysiology 38, 5 (Sept. 2001), 752--60.Google ScholarCross Ref
- Richard E. Nisbett and Timothy DeCamp Wilson. 1977. Telling more than we can know: Verbal reports on mental processes. Psychological Review 84, 3 (1977), 231--260.Google ScholarCross Ref
- Adrian M. Owen, Kathryn M. McMillan, Angela R. Laird, and Ed Bullmore. 2005. N-back working memory paradigm: A meta-analysis of normative functional neuroimaging studies. Human Brain Mapping 25, 1 (2005), 46--59.Google ScholarCross Ref
- Evan M M. Peck, Beste F. Yuksel, Alvitta Ottley, Robert J.K. Jacob, and Remco Chang. 2013. Using fNIRS brain sensing to evaluate information visualization interfaces. CHI '13 (2013), 473. Google ScholarDigital Library
- Rosalind W. Picard. 1995. Affective computing. Technical Report 321. MIT Media Laboratory.Google Scholar
- Matthew Pike, ML Wilson, Anna Divoli, and Alyona Medelyan. 2012. CUES: Cognitive Usability Evaluation System. EuroHCIR '12 (2012), 1--4.Google Scholar
- G. Michael Poor, Guy Zimmerman, Dale S. Klopfer, Samuel D. Jaffee, Laura Marie Leventhal, and Julie Barnes. 2013. Mobility Matters: Identifying Cognitive Demands That Are Sensitive to Orientation. In Interact '13, Vol. 8117 LNCS. 193--210.Google Scholar
- Felix Putze, Christoph Amma, and Tanja Schultz. 2015. Design and Evaluation of a Self-Correcting Gesture Interface based on Error Potentials from EEG. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 3375--3384. Google ScholarDigital Library
- Herbert Ramoser, Johannes Müller-Gerking, and Gert Pfurtscheller. 2000. Optimal spatial filtering of single trial EEG during imagined hand movement. IEEE Trans Rehabil Eng 8, 4 (2000), 441--446.Google ScholarCross Ref
- S Sternberg. 1966. High-speed scanning in human memory. Science (NY, N.Y.) 153 (1966), 652--654.Google Scholar
- Romain Trachel, Thomas Brochier, and Maureen Clerc. 2013. Enhancing visuospatial attention performance with brain-computer interfaces. CHI '13 (2013), 1245. Google ScholarDigital Library
- Chi Vi and Sriram Subramanian. 2012. Detecting error-related negativity for interaction design. CHI '12 (2012), 493. Google ScholarDigital Library
- J.A. Wilson, C. Guger, and G. Schalk. 2012. BCI hardware and software. In Brain-computer interfaces: principles and practice. 165--188.Google Scholar
- Dennis Wobrock, Jérémy Frey, Delphine Graef, Jean-Baptiste de la Rivi'ere, Julien Castet, and Fabien Lotte. 2015. Continuous Mental Effort Evaluation during 3D Object Manipulation Tasks based on Brain and Physiological Signals. In INTERACT '15.Google Scholar
Index Terms
- Framework for Electroencephalography-based Evaluation of User Experience
Recommendations
User experience evaluation methods: current state and development needs
NordiCHI '10: Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending BoundariesThe recent shift of emphasis to user experience (UX) has rendered it a central focus of product design and evaluation. A multitude of methods for UX design and evaluation exist, but a clear overview of the current state of the available UX evaluation ...
Understanding, scoping and defining user experience: a survey approach
CHI '09: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsDespite the growing interest in user experience (UX), it has been hard to gain a common agreement on the nature and scope of UX. In this paper, we report a survey that gathered the views on UX of 275 researchers and practitioners from academia and ...
User experience over time: an initial framework
CHI '09: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsA recent trend in Human-Computer Interaction (HCI) research addresses human needs that go beyond the instrumental, resulting in an increasing body of knowledge about how users form overall evaluative judgments on the quality of interactive products. An ...
Comments