A New Methodology of Usability Testing on the Base of the Analysis of User’s Electroencephalogram

Alfimtsev A.N.¹, Basarab M.A.^2, , Devyatkov V.V.¹ and Levanov A.A.¹

¹Department of Information Systems and Telecommunications, Bauman Moscow State Technical University, Moscow, Russia

²Department of Information Security, Bauman Moscow State Technical University, Moscow, Russia

Cite this paper:
Alfimtsev A.N., Basarab M.A., Devyatkov V.V. and Levanov A.A.. A New Methodology of Usability Testing on the Base of the Analysis of User’s Electroencephalogram. Journal of Computer Sciences and Applications. 2015; 3(5):105-111. doi: 10.12691/jcsa-3-5-1

Abstract

This paper discusses the methodology of usability testing on the base of the real-time analysis of user’s electroencephalogram (EEG). In the experimental study of the control groups of users working with a real interface of commercially relevant applications, two distinct user states were revealed which correspond to the superposition of EEG beta and delta brain waves corresponding to the so-called «calm» state and «excited» state. These states are characterized by the user experience with a friendly user interface and an interface that is considered by experts as subjectively complicated and confusing. On the basis of the obtained data, some improvements in the users interface for mobile devices were proposed, which led to a threefold increase in its CRT (click-through rate).

Keywords:
usability engineering conversion optimization usability testing electroencephalogram brain waves contextual advertising ctr user interface web interface user experience experimental research

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Figures

References:

[1]	ISO 9241-11: 1998. Ergonomic requirements for office work with visual display terminals (VDTs) – Part 11: Guidance on usability (IDT).
[2]	Jankowski, J., “Balanced approach to the design of conversion oriented websites with limited negative impact on the users”, Computational Collective Intelligence. Technologies and Applications. Lecture Notes in Computer Science, 8083, 527-536, 2013.
[3]	Borza, I. C., Macías, J.A., “Incorporating Marketing Strategies to Improve Usability Assurance in User-Centered Design Processes”, Lecture Notes in Computer Science, 9169, 152-162, 2015.
[4]	Issa, T., Turk, A., “Applying usability and HCI principles in developing marketing websites”, International Journal of Computer Information Systems and Industrial Management Applications, 4, 76-82, 2012.
[5]	Au, F.T.W., Baker, S., Warren, I., Dobbie, G., “Automated usability testing framework”, The 9th Australasian User Interface Conference (AUIC2008), Darlinghurst, Australia, 76, 55-64, 2008.
[6]	Muhi, K., Szőke, G., Fülöp, L.J., Ferenc, R., Berger, A., “A semi-automatic usability evaluation framework”, Int. Conf. on Computational Science and Its Applications (ICCSA 2013), 7972, 529-542, 2013.
[7]	Darejeh, A., Singh, D., “An investigation on Ribbon interface design guidelines for people with less computer literacy”, Computer Standards and Interfaces, 36 (5), 808-820, 2014.
[8]	Insfran, E., Fernandez, A., “A systematic review of usability evaluation in web development”, Web Information Systems Engineering – WISE 2008 Workshops. Lecture Notes in Computer Science, 5176, 81-91, 2008.
[9]	Sim, G., Read, J.C., “The Damage Index: an aggregation tool for usability problem prioritization”, The 24th BCS Interaction Specialist Group Conference, Dundee, Scotland, 54-61, 2010.
[10]	Zicklera, C., Halderb, S., Kleihb, S.C., Herbertb, C., Küblera, A., “Brain Painting: Usability testing according to the user-centered design in end users with severe motor paralysis”, Artificial Intelligence in Medicine, 59 (2), 99-110, 2013.
[11]	Nijboer, F., Clausen, J., Allison, B.Z., Haselager, P., “The Asilomar Survey: Stakeholders’ Opinions on Ethical Issues Related to Brain-Computer Interfacing”, Neuroethics, 6(3), 541-578, 2013.
[12]	Baldauf, D., Desimone, R., “Neural mechanisms of object-based attention”, Science, 344 (6182), 424-427, 2014.
[13]	Zhang, Y., Chen, Y., Bressler, S.L., Ding, M., “Response preparation and inhibition: the role of the cortical sensorimotor beta rhythm”, Neuroscience, 156 (1), 238-46, 2008.
[14]	Rao, T.K., Lakshmi, M.R., Prasad, T. V., “An Exploration on Brain Computer Interface and Its Recent Trends”, International Journal of Advanced Research in Artificial Intelligence, 1(8), 17-22, 2012.
[15]	Huang, Y., Chen, L., Luo, H., “Behavioral Oscillation in Priming: Competing Perceptual Predictions Conveyed in Alternating Theta-Band Rhythms”, The Journal of Neuroscience, 35(6), 2830-2837, 2015
[16]	Carracedo, L.M., Kjeldsen, H., Cunnington, L., Jenkins, A., Schofield, I., Cunningham, M.,O., Davies, C.H., Traub, R.D., Whittington, M.A., “A Neocortical Delta Rhythm Facilitates Reciprocal Interlaminar Interactions via Nested Theta Rhythms”, The Journal of Neuroscience, 33(26), 10750-10761, 2013.
[17]	Hu, J., Nakanishi, M., Matsumoto, K., Tagaito, H., Inoue K., “A method of usability testing by measuring brain waves”. Int. Symposium on Future Software Technology (ISFST-2000), Guiyang, China, 159-164, 2000.
[18]	Gürköka, H., Nijholta, A., “Brain–Computer Interfaces for Multimodal Interaction: A Survey and Principles”, International Journal of Human-Computer Interaction, 28 (5), 292-307, 2012.
[19]	Liao, L.-D., Lin, C.-T., McDowell, K., Wickenden, A.E., Gramann, K., Jung, T.-P., Ko, L.-W., Chang, J.-Y., “Biosensor Technologies for Augmented Brain–Computer Interfaces in the Next Decades”, Proceedings of the IEEE, 100, 1553-1566, 2012.
[20]	Lee, H. and Seo, S., “A comparison and analysis of usability methods for web evaluation: The relationship between typical usability test and bio-signals characteristics (EEG, ECG)”, Conference of the Design Research Society, Montréal, Canada, 893-904, 2010.
[21]	Chuang, J., Nguyen, H., Wang, C., and Johnson, B. “I think, therefore I am: Usability and security of authentication using brainwaves”, Lecture Notes in Computer Science, 7862, 1-16, 2013.
[22]	Bos, D.P.-O., Reuderink, B., Laar, B., Gurkok, H., Muhl, C., Poel, M., Nijholt, A., Heylen, D. “Brain-computer interfacing and games”, Brain-Computer Interfaces, 149-178, 2010.
[23]	do Amaral, V., Ferreira, L.A., Aquino, P.T., and de Castro, M.C.F., “EEG signal classification in usability experiments”, Biosignals and Biorobotics Conference (BRC), Rio de Janeiro, Brazil, 1-5, 2013.
[24]	Yoshimura, N., Satsuma, A., DaSalla, C., and Hanakawa, T., “Usability of EEG cortical currents in classification of vowel speech imagery”, International Conference on Virtual Rehabilitation (ICVR), Zurich, Switzerland, 1-2, 2011.
[25]	Nijboer, F., Laar, B., Gerritsen, S., Nijholt, A., Poel, M., “Usability of three electroencephalogram headsets for brain-computer interfaces: a within subject comparison. Interacting with computers”, 27 (5), 500-511, 2015.
[26]	Hammou, K.A., Galib, M.H., Melloul, J., “The Contributions of Neuromarketing in Marketing Research”, Journal of Management Research, 5 (4), 20-33, 2013.
[27]	Kimura, M., Uwano, H., Ohira, M., Matsumoto, K.-I., “Toward constructing an electroencephalogram measurement method for usability evaluation”, The 13th International Conference on Human-Computer Interaction, San Diego, USA, Part I: New Trends, 95-104, 2009.
[28]	“MindWave Mobile Tutorial”. Available: http://store.neurosky.com/products/mindwave-mobile-tutorial/ Accessed November 25, 2015].
[29]	Ko, A.J. , LaToza, T.D., Burnett, M.M., “A practical guide to controlled experiments of software engineering tools with human participants”, Empirical Software Engineering, 20(1), 110-141, 2015.
[30]	Tullis, T., Albert, B., “Measuring the User Experience, Second Edition: Collecting, Analyzing, and Presenting Usability Metrics”, Elsevier, 297, 2013.