Skip to main content

ProEmotion—A Tool to Tell Mobile Phone’s Gender

  • Chapter
  • First Online:
Emotional Engineering vol. 2

Abstract

Kansei engineering, also known as Kansei ergonomics or emotional engineering, aims at analyzing and incorporating customer’s feeling and demands into product function and product design. The chapter described a system called ProEmotion for the purpose of assessing the Kansei aspects of a product by considering design attributes of a product. Neural Network is used to process Kansei words. The system has been successfully implemented to ascertain gender inclination of a mobile phone. Principal parameters of a mobile are considered, that is, length, width, thickness and mass. The system can inform gender inclination of a mobile phone with accuracy up to 90 %. This is based on a set of 92 mobile phone samples from the five major mobile phone manufacturers.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Nagamachi M (1989) Kansei engineering. Kaibundo Publishing, Tokyo

    Google Scholar 

  2. Nagamachi M (1991) An image technology expert system and its application to design consultation. Int J Hum-Comput Interact 3(3):267–279

    Article  MathSciNet  Google Scholar 

  3. Nagamachi M (1995a) Kansei engineering: a new ergonomic consumer-oriented technology for product development. Int J Ind Ergon 15(1):3–11

    Google Scholar 

  4. Barnes C, Lillford SP (2009) Decision support for the design of affective products. J Eng Des 20(5):477–492

    Article  Google Scholar 

  5. Choi K, Jun C (2007) A systematic approach to the Kansei factors of tactile sense regarding the surface roughness. Appl Ergon 38(1):53–63

    Article  Google Scholar 

  6. Fukushima K, Kawata H, Fujiwara Y, Genno H (1995) Human sensory perception oriented image processing in a color copy system. Int J Ind Ergon 15(1):63–74

    Google Scholar 

  7. McDonagh D, Bruseberg A, Haslam C (2002) Visual product evaluation: exploring users’ emotional relationships with products. Appl Ergon 33(3):231–240

    Article  Google Scholar 

  8. Nagamachi M (2002) Kansei engineering as a powerful consumer-oriented technology for product development. Appl Ergon 33(3):289–294

    Google Scholar 

  9. Hohenegger J, Bufardi A, Xirouchakis P (2007) A new concept of compatibility structure in new product development. Adv Eng Inform 21(1):101–116

    Article  Google Scholar 

  10. Nagamachi M (1995) Introduction of Kansei Engineering. J Indus Ergon 15(1):13–24

    Article  MathSciNet  Google Scholar 

  11. Ishihara S, Ishihara K, Nagamachi M (1998) Kansei inference system and internet VR. Manuf Hybrid Automation-II. J Indus Ergon 15(1):63–74, pp 403–406

    Google Scholar 

  12. Koda Y, Kanaya I, Sato K (2007) Modeling real objects for Kansei-based shape retrieval. Int J Autom Comput 4(1):14–17

    Article  Google Scholar 

  13. Lee JWT, Chan SCF, Yeung DS (1995) Modelling constraints in part structures. Comput Ind Eng 28(3):645–657

    Article  Google Scholar 

  14. Leon N (2009) The future of computer-aided innovation. Comput Ind 60(8):539–550

    Article  Google Scholar 

  15. Peak RS, Lubell J, Srinivasan V, Waterbury SC (2004) STEP, XML, and UML: complementary technologies. J Comput Inf Sci Eng 4(4):379–390

    Article  Google Scholar 

  16. Stouffs R (2008) Constructing design representations using a sortal approach. Adv Eng Inform 22(1):71–89

    Article  Google Scholar 

  17. Wilson JR (1999) Virtual environments applications and applied ergonomics. Appl Ergonomics 30:3–9

    Article  Google Scholar 

  18. Zhai LY, Khoo LP, Zhong ZW (2009) A dominance-based rough set approach to Kansei Engineering in product development. Expert Syst Appl 36(1):393–402

    Article  Google Scholar 

  19. Kuang J, Jiang P (2009) Product platform design for a product family based on Kansei engineering. J Eng Des 20(6):589–607

    Article  Google Scholar 

  20. Lai HH, Lin YC, Yeh CH, Wei CH (2006) User-oriented design for the optimal combination on product design. Int J Prod Econ 100(2):253–267

    Article  Google Scholar 

  21. Lai HH, Chang YM, Chang HC (2005) A robust design approach for enhancing the feeling quality of a product: a car profile case study. Int J Ind Ergon 35(5):445–460

    Article  Google Scholar 

  22. Lin YC, Lai HH, Yeh CH (2007) Consumer-oriented product form design based on fuzzy logic: a case study of mobile phones. Int J Ind Ergon 37(6):531–543

    Article  Google Scholar 

  23. Matsubara Y, Nagamachi M (1997) Hybrid Kansei Engineering System and design support. Int J Ind Ergon 19(2):81–92

    Google Scholar 

  24. Nagamachi M (2000) Application of Kansei engineering and concurrent engineering to a cosmetic product. In: Proceedings of the ERGON-AXIA–2000, Warsaw, Poland, May 2000

    Google Scholar 

  25. Nagamachi M, Nishino T (1999) HousMall: an application of Kansei engineering to house design consultation. In: Proceedings of the international conference on TQM and human factors, Linkoping, Sweden, pp 349–354

    Google Scholar 

  26. Ogawa T, Nagai Y, Ikeda M (2009) An ontological approach to designers’ idea explanation style: towards supporting the sharing of Kansei-ideas in textile design. Adv Eng Inform 23(2):157–164

    Article  Google Scholar 

  27. Roy R, Goatman M, Khangura K (2009) User-centric design and Kansei Engineering. CIRP J Manuf Sci Technol 1(3):172–178

    Article  Google Scholar 

  28. Schutte S, Eklund J (2005) Design of rocker switches for work-vehicles: an application of Kansei engineering. Appl Ergon 36(5):557–567

    Article  Google Scholar 

  29. Akioka S, Fukumori H, Muraoka Y (2009) Search in the mood: the information filter based on ambiguous queries. Int J Comput Appl Technol 34(4):322–329

    Article  Google Scholar 

  30. Bahn S, Lee C, Nam CS, Yun MH (2009) Incorporating affective customer needs for luxuriousness into product design attributes. Hum Factors Ergon Manuf 19(2):105–127

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to William Wei-Lin Wang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag London

About this chapter

Cite this chapter

Wang, W.WL., Hsiao, HH., Xu, X.W. (2013). ProEmotion—A Tool to Tell Mobile Phone’s Gender . In: Fukuda, S. (eds) Emotional Engineering vol. 2. Springer, London. https://doi.org/10.1007/978-1-4471-4984-2_7

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-4984-2_7

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4983-5

  • Online ISBN: 978-1-4471-4984-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics