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Taking the Subjectivity out of UX Evaluation with Emotiv EPOC+

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Published:17 September 2019Publication History

ABSTRACT

Changes in the contemporary business environment are shifting the focus of designers and developers of Information Systems (IS) from a narrow focus on system usability to an overall user experience (UX). The subjective nature of UX meant that the majority of UX evaluation methods are subjective. However, advancements in new technologies now make it possible to evaluate UX objectively by collecting physiological data unobtrusively. In this study we explored the use of the Emotiv EPOC+ headset to collect electro-encephalography (EEG) patterns to 'examine' brain activities to determine the presence or absence of the emotion of anger, as well as 'performance metrics' on engagement, excitement, interest, focus, relaxation, and stress, in order to evaluate UX. The results showed that the Emotiv EPOC+ headset provides a low-cost means of evaluating UX objectively.

References

  1. D. L. Scapin, B. Senach, B. Trousse, and M. Pallot, "User experience: buzzword or new paradigm?." pp. 336--341, Proceedings of the 5th International Conference on Advances in Computer-Human Interactions (ACHI 2012), 2012.Google ScholarGoogle Scholar
  2. M. Hassenzahl, and N. Tractinsky, "User experience - a research agenda," Behaviour & Information Technology, vol. 25, no. 2, pp. 91--97, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  3. E. L.-C. Law, V. Roto, M. Hassenzahl, A. P. Vermeeren, and J. Kort, "Understanding, scoping and defining user experience: a survey approach." pp. 719--728, Proceedings of the SIGCHI conference on human factors in computing systems, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. A. Bruun, M. K. Larusdottir, L. Nielsen, P. A. Nielsen, and J. S. Persson, "The role of UX professionals in agile development: a case study from industry ". pp. 352--363, Proceedings of the 10th Nordic Conference on Human-Computer Interaction, Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. M. Hassenzahl, "User experience (UX): towards an experiential perspective on product quality," in 20th Conference on I'Interaction Homme-Machine, Metz, France, 2008, pp. 11--15. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. International organization for standardization. "Ergonomics of human-system: Human-centred design for interactive systems," Retrieved on 04/04/19, from 2010.Google ScholarGoogle Scholar
  7. K. Kuusinen, and K. Väänänen-Vainio-Mattila, "How to make agile UX work more efficient: management and sales perspectives," in Proceedings of the 7th Nordic Conference on Human-Computer Interaction: Making Sense Through Design, Copenhagen, Denmark, 2012, pp. 139--148. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. C. Ardito, P. Buono, D. Caivano, M. F. Costabile, and R. Lanzilotti, "Investigating and Promoting UX Practice in Industry: An Experimental Study," International Journal of Human-Computer Studies, vol. 72, no. 6, pp. 542--551, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  9. T. Guidini Gonçalves, K. Marçal de Oliveira, and C. Kolski, "HCI in Practice: An Empirical Study with Software Process Capability Maturity Model Consultants in Brazil," Journal of Software: Evolution and Process, vol. 30, no. 11, pp. e2109, 2018.Google ScholarGoogle ScholarCross RefCross Ref
  10. A. Bilgihan, "Gen Y customer loyalty in online shopping: an integrated model of trust, user experience and branding," Computers in Human Behavior, vol. 61, pp. 103--113, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. G. Paunovic. "The bottom line: why good UX design means better business " Retrieved on 04/04/19, from https://www.forbes.com/sites/forbesagencycouncil/2017/03/23/the-bottom-line-why-good-ux-design-means-better-business/#72d73cdf2396 2017.Google ScholarGoogle Scholar
  12. A. A. Ogunyemi, D. Lamas, E. R. Adagunodo, F. Loizides, and I. B. Da Rosa, "Theory, practice and policy: an inquiry into the uptake of HCI practices in the software industry of a developing country," International Journal of Human-Computer Interaction, vol. 32, no. 9, pp. 665--681, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  13. M. Minge, and M. Thüring, "Hedonic and pragmatic halo effects at early stages of User Experience," International Journal of Human-Computer Studies, vol. 109, no. 2018, pp. 13--25, 2018. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. G. Brajnik, and C. Giachin, "Using sketches and storyboards to assess impact of age difference in user experience," International Journal of Human-Computer Studies, vol. 72, no. 6, pp. 552--566, 2014/06/01/, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  15. P. Desmet, and P. Hekkert, "Framework of product experience," International Journal of Design, vol. 1, no. 1, pp. 57--66, 2007.Google ScholarGoogle Scholar
  16. V. Balasubramoniam, and N. Tungatkar, "Study of user experience (UX) and UX evaluation methods," International Journal of Advanced Research in Computer Engineering & Technology, vol. 2, no. 3, pp. 1214--1219, 2013.Google ScholarGoogle Scholar
  17. R. L. Mandryk, K. M. Inkpen, and T. W. Calvert, "Using psychophysiological techniques to measure user experience with entertainment technologies," Behaviour & Information Technology, vol. 25, no. 2, pp. 141--158, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  18. M. Van Camp, M. De Boeck, S. Verwulgen, and G. De Bruyne, "EEG technology for UX evaluation: A mltisensory perspective," Advances in Neuroergonomics and Cognitive Engineering. pp. 337--343, Proceedings of the 2019.Google ScholarGoogle Scholar
  19. P. M. Podsakoff, S. B. MacKenzie, J.-Y. Lee, and N. P. Podsakoff, "Common method biases in behavioral research: a critical review of the literature and recommended remedies," Journal of Applied Psychology, vol. 88, no. 5, pp. 879--903, 2003.Google ScholarGoogle ScholarCross RefCross Ref
  20. B. A. Olken, "Corruption perceptions vs. corruption reality," Journal of Public Economics, vol. 93, no. 7, pp. 950--964, 2009/08/01/, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  21. D. Zimprich, and T. Kurtz, "Subjective and Objective Memory Changes in Old Age across Five Years," Gerontology, vol. 61, no. 3, pp. 223--231, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  22. F. F. Morgado, J. F. Meireles, C. M. Neves, A. C. Amaral, and M. E. Ferreira, "Scale development: ten main limitations and recommendations to improve future research practices," Psicologia: Reflexão e Crítica, vol. 30, no. 3, 2017.Google ScholarGoogle Scholar
  23. C. A. Latkin, C. Edwards, M. A. Davey-Rothwell, and K. E. Tobin, "The relationship between social desirability bias and self-reports of health, substance use, and social network factors among urban substance users in Baltimore, Maryland," Addictive Behaviors, vol. 73, pp. 133--136, 2017/10/01/, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  24. L. Vokorokos, B. Madoš, N. Ádám, and A. Baláž, "Data acquisition in noninvasive brain-computer interface using Emotiv EPOC neuroheadset," Acta Electrotechnica et Informatica, vol. 12, no. 1, pp. 5--8, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  25. N. Vala, and K. Trivedi, "Brain computer interface: data acquisition using noninvasive Emotiv EPOC neuroheadset," International Journal of Software & Hardware Research in Engineering, vol. 2, no. 5, pp. 127--130, 2014.Google ScholarGoogle Scholar
  26. R. L. Hazlett, and J. Benedek, "Measuring emotional valence to understand the user's experience of software," International Journal of Human-Computer Studies, vol. 65, no. 4, pp. 306--314, 2007/04/01/, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. J. Brosens, F. Adebesin, and R. Kruger, "In the eye of the beholder: Teaching user centred design to information and communication technology students with the help of Eye Tracking," Handbook of Research on Diverse Teaching Strategies for the Technology-Rich Classroom, L. Tomei, ed., IGI, In Press.Google ScholarGoogle Scholar
  28. C. Lallemand, G. Gronier, and V. Koenig, "User experience: A concept without consensus? Exploring practitioners' perspectives through an international survey," Computers in Human Behavior, vol. 43, pp. 35--48, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. M. Thuring, and S. Mahlke, "Usability, aesthetics and emotions in human-technology," International Journal of Psycholohgy, pp. 12, 2007.Google ScholarGoogle Scholar
  30. M. D. Good, J. A. Whiteside, D. R. Wixon, and S. J. Jones, "Building a user-derived interface," Communications of the ACM, vol. 27, no. 10, pp. 1032--1043, 1984. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. V. Roto, "User experience building blocks," Proceedings of the The 2nd COST294-MAUSE International Open Workshop, 2006.Google ScholarGoogle Scholar
  32. N. Fragopanagos, and J. G. Taylor, "Emotion recognition in human-computer interaction," Neural Networks, vol. 18, no. 4, pp. 389--405, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. A. Agarwal, and A. Meyer, "Beyond usability: evaluating emotional response as an integral part of the user experience," in CHI '09 Extended Abstracts on Human Factors in Computing Systems, Boston, MA, USA, 2009, pp. 2919--2930. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. I. B. Mauss, and M. D. Robinson, "Measures of emotion: A review," Cognition and Emotion, vol. 23, no. 2, pp. 209--237, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  35. S. Brave, and C. Nass, "Emotion in human-computer interaction," Handbook of human-computer interaction, J. Jacko and A. Sears, eds., pp. 251--271: Lawrence Erlbaum Associates 2002.Google ScholarGoogle Scholar
  36. C. Peter, and R. Beale, "Affect and emotion in human-computer interaction," Expanding the frontiers of visual analytics and visualization D. J. Earnshaw, R. Kasik, J. Vince and P. C. Wong, eds., Springer, 2012, pp. 239--262.Google ScholarGoogle Scholar
  37. D. Watson, D. Wiese, J. Vaida, and A. Tellegen, "The two general activation systems of affect: structural findings, evolutionary considerations, and psychobiological evidence," Journal of Personality and Social Psychology, vol. 76, no. 5, pp. 820--838, 1999.Google ScholarGoogle ScholarCross RefCross Ref
  38. N. Tromp, P. Hekkert, and P.-P. Verbeek, "Design for socially responsible behavior: a classification of influence based on intended user experience," Design Issues, vol. 27, no. 3, pp. 3--19, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  39. P. J. Lang, "The emotion probe: Studies of motivation and attention," American psychologist, vol. 50, no. 5, pp. 372, 1995.Google ScholarGoogle ScholarCross RefCross Ref
  40. K. Nesbitt, K. Blackmore, G. Hookham, F. Kay-Lambkin, and P. Walla, "Using the Startle Eye-Blink to Measure Affect in Players," Serious Games Analytics: Methodologies for Performance Measurement, Assessment, and Improvement, C. S. Loh, Y. Sheng and D. Ifenthaler, eds., pp. 401--434, Cham: Springer International Publishing, 2015.Google ScholarGoogle Scholar
  41. O. Villon, and C. Lisetti, "A user model of psycho-physiological measure of emotion," Proceedings of the 11th International Conference on User Modeling (UM2007), 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. K. Väänänen-Vainio-Mattila, V. Roto, and M. Hassenzahl, "Towards practical user experience evaluation methods," Meaningful measures: Valid useful user experience measurement (VUUM), pp. 19--22, 2008.Google ScholarGoogle Scholar
  43. Y.-P. Lin, C.-H. Wang, T.-P. Jung, T.-L. Wu, S.-K. Jeng, J.-R. Duann, and J.-H. Chen, "EEG-based emotion recognition in music listening," IEEE Transactions on Biomedical Engineering, vol. 57, no. 7, pp. 1798--1806, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  44. M. Williamson, "Emotions, reason and behaviour: A search for the truth," Journal of Consumer Behaviour, vol. 2, no. 2, pp. 196--202, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  45. U. R. Acharya, F. Molinari, S. V. Sree, S. Chattopadhyay, K.-H. Ng, and J. S. Suri, "Automated diagnosis of epileptic EEG using entropies," Biomedical Signal Processing and Control, vol. 7, no. 4, pp. 401--408, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  46. J. Kosiński, K. Szklanny, A. Wieczorkowska, and M. Wichrowski, "An analysis of game-related emotions using Emotiv EPOC." pp. 913--917, Proceedings of the Federated Conference on Computer Science and Information Systems, 2018.Google ScholarGoogle Scholar
  47. P. C. Petrantonakis, and L. J. Hadjileontiadis, "A novel emotion elicitation index using frontal brain asymmetry for enhanced EEG-based emotion recognition," IEEE Transactions on information technology in biomedicine, vol. 15, no. 5, pp. 737--746, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. K. Stytsenko, E. Jablonskis, and C. Prahm, "Evaluation of consumer EEG device Emotiv EPOC," Proceedings of the MEi: CogSci Conference 2011, Ljubljana, 2011.Google ScholarGoogle Scholar
  49. N. A. Badcock, P. Mousikou, Y. Mahajan, P. De Lissa, J. Thie, and G. McArthur, "Validation of the Emotiv EPOC® EEG gaming system for measuring research quality auditory ERPs," PeerJ, vol. 1, pp. e38, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  50. R. Lievesley, M. Wozencroft, and D. Ewins, "The Emotiv EPOC neuroheadset: an inexpensive method of controlling assistive technologies using facial expressions and thoughts?," Journal of Assistive Technologies, vol. 5, no. 2, pp. 67--82, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  51. A. Kawala-Janik, M. Podpora, A. Gardecki, W. Czuczwara, J. Baranowski, and W. Bauer, "Game controller based on biomedical signals." pp. 934--939, Proceedings of the 20th International Conference on Methods and Models in Automation and Robotics (MMAR), 2015.Google ScholarGoogle Scholar
  52. T. McMahan, I. Parberry, and T. D. Parsons, "Modality specific assessment of video game player's experience using the Emotiv," Entertainment Computing, vol. 7, pp. 1--6, 2015/03/01/, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  53. D. Boucha, A. Amiri, and D. Chogueur, "Controlling electronic devices remotely by voice and brain waves." pp. 38--42, Proceedings of the 2017 International Conference on Mathematics and Information Technology (ICMIT), 2017.Google ScholarGoogle Scholar
  54. A. E. Alchalcabi, A. N. Eddin, and S. Shirmohammadi, "More attention, less deficit: Wearable EEG-based serious game for focus improvement." pp. 1--8, Proceedings of the 2017 IEEE 5th International Conference on Serious Games and Applications for Health (SeGAH), 2017.Google ScholarGoogle ScholarCross RefCross Ref

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    • Published in

      cover image ACM Other conferences
      SAICSIT '19: Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019
      September 2019
      352 pages
      ISBN:9781450372657
      DOI:10.1145/3351108

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      Publication History

      • Published: 17 September 2019

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