Abstract
KANSEI Engineering (KE) [1] was created at Hiroshima University about 30 year ago and it is well known in the world at present as an ergonomic customer-oriented product development technology. It is a method for translating sensations and impressions into product parameters. The objective of KE is to study the relationship between product forms and KANSEI images. However, the KE method is based on the analysis of human subjective factors, customer’s psychological feelings and needs, which is transformed in product design parameters. The customer’s psychological feelings and needs are usually acquired by subjective tools. The questions which arises is if these subjective tools reflect the real customer needs. Nowadays, some scholars have recently started using biofeedback to evaluate the emotions of human interaction with products. Some studies have shown that EEG and Infrared Thermography measurements can help reduce subjective interpretation in data and improve user perception in their interactions with products. This systematic literature review aims to search the references on EEG, Infrared Thermography, Kansei Engineering and emotion. It will serve as a support for further researches to check if is possible to include biofeedback tools to contribute to subjective analyzes.
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References
Schütte, S.T.W., Eklund, J., Axelsson, J.R.C., et al.: Concepts, methods and tools in Kansei engineering. Theor. Issues Ergon. Sci. 5(3), 214–231 (2004)
Lietz, P.: Research into questionnaire design. Int. J. Market Res. 52(2), 249–272 (2010)
Bradley, M.M., Lang, P.J.: Measuring emotion: the self-assessment Manikin and the semantic differential. J. Behav. Ther. Exp. Psychiatry 25(1), 49–59 (1994)
Karsaklian, E., Sorbello, C., Sorbello, A.: Mapping the pathway to emotional engagement a methodology to create the emotional engagement model. J. Acad. Bus. Econ. 17, 47–56 (2017)
Greene, B.A.: Measuring cognitive engagement with self-report scales: reflections from over 20 years of research. Educ. Psychol. 50(1), 14–30 (2015)
Barros, R.Q., Santos, G., Ribeiro, C., Torres, R., Barros, M.Q., Soares, M.M.: A usability study of a brain-computer interface apparatus: an ergonomic approach. In: Marcus, A. (ed.) DUXU 2015. LNCS, vol. 9186, pp. 224–236. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-20886-2_22
Barros, R.Q., et al.: Analysis of product use by means of eye tracking and EEG: a study of neuroergonomics. In: Marcus, A. (ed.) DUXU 2016. LNCS, vol. 9747, pp. 539–548. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-40355-7_51
Wimmer, K., Stiles, J.: The observational research handbook: understanding how consumers live with your products. J. Advert. Res. 41(1), 91–93 (2001)
Creusen, M., Hultink, E.J., Eling, K.: Choice of consumer research methods in the front end of new product development. Int. J. Market Res. 55(1), 81–104 (2013)
Bruseberg, A., McDonagh-Philp, D.: Focus groups to support the industrial/product designer: a review based on current literature and designers’ feedback. Appl. Ergon. 33(1), 27–38 (2002)
Gaver, W.W.: Cultural probes and the value of uncertainty. Interactions 11(5), 53–56 (2004)
Oliveira, T., Noriega, P., Rebelo, F., Heidrich, R.: Evaluation of the relationship between virtual environments and emotions. In: Rebelo, F., Soares, M. (eds.) AHFE 2017. AISC, vol. 588, pp. 71–82. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-60582-1_8
Trindade, Y., Rebelo, F., Noriega, P.: Potentialities of a face reading tool to a digital game evaluation and development: a preliminary study. In: Rebelo, F., Soares, M. (eds.) AHFE 2017. AISC, vol. 588, pp. 371–381. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-60582-1_37
Slobounov, S.M., Ray, W., Johnson, B., et al.: Modulation of cortical activity in 2D versus 3D virtual reality environments: an EEG study. Int. J. Psychophysiol. 95(3), 254–260 (2015)
Guo, F., et al.: Distinguishing and quantifying the visual aesthetics of a product: an integrated approach of eye-tracking and EEG. Int. J. Ind. Ergon. 71, 47–56 (2019)
Soares, M.M., Vitorino, D.F., Marçal, M.A.: Application of digital infrared thermography for emotional evaluation: a study of the gestural interface applied to 3D modeling software. In: Rebelo, F., Soares, M.M. (eds.) AHFE 2018. AISC, vol. 777, pp. 201–212. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-94706-8_23
Cook, D.J.: Systematic reviewes: synthesis of best evidence for clinical decisions. Ann. Intern. Med. 126(5), 376 (1997)
Blum, A., Merino, E.A.D., Merino, G.S.A.D.: Visual method for systematic review in design based on concepts of Data Mining. Eugenio Andrés Díaz Merino DAPesquisa 11(16), 124–139 (2016)
Web of Science (2020). www.isiknowledge.com. Accessed 16 Jan 2020
Elsevier (2020). https://www.sciencedirect.com. Accessed 16 Jan 2020
ACM (2020). https://dl.acm.org. Accessed 16 Jan 2020
LNCS (2020). http://www.springer.com/lncs. Accessed 16 Jan 2020
Scopus (2020). https://www.scopus.com. Accessed 16 Jan 2020
Jenkins, S., Brown, R., Rutterford, N.: Comparing thermographic, EEG, and subjective measures of affective experience during simulated product interactions. Int. J. Des. 3(2), 53–65 (2009)
Jenkins, S., Brown, R., Rutterford, N.: Comparison of thermographic, EEG and subjective measures of affective experience of designed stimuli. In: Proceedings from the 6th Conference on Design and Emotion (2008)
Abstract of the joint meetings of the 23rd annual meeting of the Japan neuroscience society and the 10th annual meeting of the Japanese neural network society, 4–6 September 2000, Yokohama, Japan. Plenary Lecture. Neurosci. Res. 38(Suppl. 1), pp. S1–S189 (2000)
Yamagishi, M., Jingu, H., Kasamatsu, K., Kiso, H., Fukuzumi, S.: Proposal for indices to assess attractiveness on initial use of mobile phones. In: Marcus, A. (ed.) DUXU 2011. LNCS, vol. 6769, pp. 696–705. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21675-6_79
Volpe, G., Camurri, A.: A system for embodied social active listening to sound and music content. J. Comput. Cult. Heritage 4(1), 1–23 (2011)
Ertin, E., Arora, A., Ramnath, R., et al.: Kansei: a testbed for sensing at scale. In: Proceedings of the 5th International Conference on Information Processing in Sensor Networks (IPSN 2006), pp. 399–406. ACM, New York (2006)
Sridharan, M., Bapat, S., Ramnath, R., et al.: Implementing an autonomic architecture for fault-tolerance in a wireless sensor network testbed for at-scale experimentation. In: Proceedings of the 2008 ACM Symposium on Applied Computing (SAC 2008), pp. 1670–1676. ACM, New York (2008)
Barros, R.Q., Soares, M.M., Maçal, M.A., et al.: Using digital thermography to analyse the product user’s affective experience of a product. In: Rebelo, F., Soares, M. (eds.) Advances in Ergonomics in Design. Advances in Intelligent Systems and Computing, vol. 485, pp. 97–107. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-41983-1_10
Nozawa, A., Takei, Y.: Dynamic analysis of dorsal thermal images. Artif. Life Rob. 16(2), 147–151 (2011)
Nacke, L.E.: Wiimote vs. controller: electroencephalographic measurement of affective gameplay interaction. In: Proceedings of the International Academic Conference on the Future of Game Design and Technology (Futureplay 2010), pp. 159–166. ACM, New York (2010)
Jaichandar, K.S., Elara, M.R., García, E.A.M.: Investigation of facial infrared thermography during interaction with therapeutic pet robot during cognitive training: a quantitative approach. In: Proceedings of the 6th International Conference on Rehabilitation Engineering & Assistive Technology (i-CREATe 2012), Article 28, pp. 1–4. Singapore Therapeutic, Assistive & Rehabilitative Technologies (START) Centre, Midview City (2012)
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Zeng, J., Soares, M.M., He, R. (2020). Systematic Review on Using Biofeedback (EEG and Infrared Thermography) to Evaluate Emotion and User Perception Acquired by Kansei Engineering. In: Marcus, A., Rosenzweig, E. (eds) Design, User Experience, and Usability. Interaction Design. HCII 2020. Lecture Notes in Computer Science(), vol 12200. Springer, Cham. https://doi.org/10.1007/978-3-030-49713-2_40
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