Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-26T12:46:52.501Z Has data issue: false hasContentIssue false
  • English
  • Français

A Concept for Physiological User Description in the Context of Dual User Integration

Part of: User-Centred Design

Published online by Cambridge University Press:  26 July 2019

Tina Schröppel ,
Theresia Diepold ,
Jörg Miehling  and
Sandro Wartzack

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In order to ensure the user's acceptance towards a product, the user has to be captured with all his facets and requirements. In this context, many user-centred design methods only focus on single aspects such as subjective expectation or ergonomic product design. Correlations and connections or a common consideration of several user parameters are often neglected, even if this can provide useful information for improving the design of products. Dual user integration tries to close this gap to a certain extent and considers the user's subjective expectation in combination with their physiological capacities. An integral part of this approach is a target-oriented evaluation of the user. Currently available methods of physiological and subjective evaluation of the user are only partially applicable for dual user integration. Especially physiological measurement techniques are time-consuming and expensive. For this reason, this contribution presents a new concept for capturing and describing the physiological capacity of the user via semantic differentials. Thereby, motor functions, cognition and perception are considered.

Keywords

User centred designDesign methodsIntegrated product developmentDual user integrationPhysiological user description
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 3791 - 3800
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Balters, S., Bisballe Jensen, M. and Steinert, M. (2015), “Physiological and Sensorial Based Quantification of Human-Object-Interaction-the QOSI Matrix”, In: Weber, C., Husung, S., Cascini, G., Cantamessa, M., Marjanović, D. and Bordegoni, M. (Ed.), Proceedings of the 20th International Conference on on Engineering Design (ICED15) Vol 11: Human Behaviour in Design, Design Education, Milan, 27.-30.07.2015, Design Society, Glasgow, pp. 121–132.Google Scholar
Bös, K., Abel, T., Woll, A., Niemann, S., Tittlbach, S. and Schott, N. (2002), “Der Fragebogen zur Erfassung des motorischen Funktionsstatus (FFB-Mot)”, Diagnostica, Vol. 48 No. 2, pp. 101–111.Google Scholar
Bös, K. and Mechling, H. (1983), Dimensionen sportmotorischer Leistungen, Hofmann, Schorndorf.Google Scholar
Bubb, H., Popova-Dlugosch, S. and Breuninger, J. (2016), “Ergonomische Produktgestaltung”, In: Lindemann, U. (Ed.), Handbuch Produktentwicklung, Carl Hanser Verlag, München, pp. 837–865.Google Scholar
Desmet, P.M.A. and Pohlmeyer, A.E. (2013), “Positive Design: An Introduction to Design for Subjective Well-Being”, International Journal of Design, Vol. 7 No. 3, pp. 5–19.Google Scholar
DIN (2008), Ergonomie – Körpermaße des Menschen – Teil 1: Begriffe, Messverfahren No. DIN 33402-1, Beuth, Berlin.Google Scholar
DIN (2017), Wesentliche Maße des menschlichen Körpers für die technische Gestaltung – Teil 1: Körpermaßdefinitionen und -messpunkte No. DIN EN ISO 7250-1, Beuth, Berlin.Google Scholar
Folstein, M.F., Folstein, S.E. and McHugh, P.R. (1975), “Mini-mental state. A practical method for grading the cognitive state of patients for the clinician”, Journal of Psychiatric Research, Vol. 12 No. 3, pp. 189–198.Google Scholar
Frey, B. (1993), Zur Bewertung von Anmutungsqualitäten, Beiträge zum Produkt-Marketing, Vol. 22, Förderges, Produkt-Marketing, Köln.Google Scholar
Goldberg, L.R. (1990), “An Alternative “Description of Personality”: The Big-Five Factor Structure”, Journal of Personality and Social Psychology, Vol. 59 No. 6, pp. 1216–1229.Google Scholar
Goodman, J., Langdon, P. and Clarkson, P.J. (2007), “Formats for User Data in Inclusive Design”, In: Stephanidis, C. (Ed.), Universal access in human computer interaction, Lecture Notes in Computer Science, Vol. 4554, Springer, Berlin, pp. 117–126.Google Scholar
Götze, R., Zenz, K. and Michal, C. (2005), Neuropsychologisches Befundsystem für die Ergotherapie, 2nd ed., Springer, Heidelberg.Google Scholar
Güllich, A. and Krüger, M. (2013), Sport, Springer, Berlin, Heidelberg.Google Scholar
Hotzman, J., Gordon, C.C., Bradtmiller, B., Corner, B.D., Mucher, M., Kristensen, S., Paquette, S. and Blackwell, C.L. (2011. Measurer's Handbook: US Army and Marine Corps Anthropometric Survey, Available at: http://www.dtic.mil/dtic/tr/fulltext/u2/a548497.pdf.Google Scholar
Kett, S.G. and Wartzack, S. (2016), Considering Emotional Impressions in Product Development: Quality of Life Theory and Its Impact on Design Strategy, 16.-19.05.2016, Dubrovnik, Croatia.Google Scholar
Kliegel, M. and Jäger, T. (2006), “Die Entwicklung des prospektiven Gedächtnisses über die Lebensspanne”, Zeitschrift für Entwicklungspsychologie und Pädagogische Psychologie, Vol. 38 No. 4, pp. 162–174.Google Scholar
Kotler, P. and Armstrong, G. (2016), Principles of marketing, 16 ed., Pearson, Harlow.Google Scholar
Meinel, K. and Schnabel, G. (2018), Bewegungslehre - Sportmotorik: Abriss einer Theorie der sportlichen Motorik unter pädagogischem Aspekt, Meyer & Meyer Verlag, Aachen.Google Scholar
Miehling, J., Schuhhardt, J., Paulus-Rohmer, F. and Wartzack, S. (2015), “Computer Aided Ergonomics Through Parametric Biomechanical Simulation”, ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Boston, Massachusetts, USA, August 2-5, 2015, American Society of Mechanical Engineers, New York.Google Scholar
OECD (2013), OECD Guidelines on Measuring Subjective Well-being, OECD Publishing, Paris.Google Scholar
Osgood, C.E. (1957), The measurement of meaning, University of Illinois Press, Urbana.Google Scholar
Robins, R.W., Tracy, J.L. and Sherman, J.W. (2016), “What kinds of methods do personality psychologists use? A survey of Journal Editors and editorial board members”, In: Robins, R.W., Fraley, R.C. and Krueger, R.F. (Ed.), Handbook of research methods in personality psychology, Guilford, New York, London, pp. 673–678.Google Scholar
Russell, J.A. (1980), “A Circumplex Model of Affect”, Journal of Personality and Social Psychology, Vol. 39 No. 6, pp. 1161–1178.Google Scholar
Schlick, C.M., Bruder, R. and Luczak, H. (2010), Arbeitswissenschaft, Springer Berlin Heidelberg, Berlin, Heidelberg.10.1007/978-3-540-78333-6Google Scholar
Schmerling, D. (2013), The Measurement Of Motivation: Examining The Measurement Properties Of The Motivation Assessment System, Dissertation, Department of Industrial and Organizational Psychology, University of Central Florida, Orlando.Google Scholar
Schröppel, T., Miehling, J. and Wartzack, S. (2019), Roadmap für die Entwicklung einer Methodik zur dualen Nutzerintegration, Stuttgarter Symposium für Produktentwicklung. 16.05.2019, Stuttgart, accepted Paper.Google Scholar
Schröppel, T. and Wartzack, S. (2018), “Making a difference: Integrating physiological and psychological needs in user description”, In: Ekströmer, P., Schütte, Simon and Ölvander, Johan (Ed.), Proceedings of NordDesign 2018, Linköping, Sweden, 14th - 17th August 2018, LiU Tryck, Linköping, pp. 1–10.Google Scholar
Wakula, J., Berg, K., Schaub, K., Bruder, R., Glitsch, U., Ellegast, R., and Institut für Arbeitswissenschaft der TU Darmstadt, BGIA and Unfallversicherung Sankt Augustin (2009), Der montagespezifische Kraftatlas, Technische Informationsbibliothek u. Universitätsbibliothek; BGIA, Hannover, Sankt Augustin.Google Scholar
Wall, M. and Sadun, A.A. (1989), New Methods of Sensory Visual Testing, Springer, New York.Google Scholar
Wentura, D. and Degner, J. (2006), “Indirekte Messung von Einstellungen mit kognitionspsychologischen Verfahren: Chancen und Probleme”, In: Witte, E.H. (Ed.), Evolutionäre Sozialpsychologie und automatische Prozesse: Beiträge des 21. Hamburger Symposions zur Methodologie der Sozialpsychologie, Pabst Science Publ, Lengerich.Google Scholar
Wickens, C.D., Lee, J.D., Liu, Y. and Gordon Becker, S.E. (2004), An introduction to human factors engineering, 2nd ed., Pearson Prentice Hall, Upper Saddle River, N.J.Google Scholar
Zöller, S.G. and Wartzack, S. (2017), “Considering Users’ Emotions in Product Development Processes and the Need to Design for Attitudes”, In: Fukuda, S. (Ed.), Emotional Engineering, 5th ed., Springer, Cham, pp. 69–97.Google Scholar