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The influence of curvature and proportion on emotional preference for human-machine interface design

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Abstract

Previous studies had found that people preferred curved visual objects. This study aimed to explore the relationship between curvature and proportion of human-machine interface and emotional preference based on Kansei Engineering. First, through the survey, the five groups of target emotional images of human-machine interface were deduced: Safe - Dangerous, Rigorous - Lively, Masculine - Feminine, Cold - Warm, and Soft - Hard. Secondly, different curvature and proportion levels were used as stimuli to explore their influence on emotional preference. Participants in the experiment interacted with the prototype of human-machine interface samples, and provide Likert scale scores about emotional preference for each sample. Then, based on analysis of variance and factor analysis, the subjects’ perception to the evaluated interface was revealed. In Study 1, one-way analysis of variance studied the influence of curvature levels of human-machine interface on emotional preference. The results showed that curvature was positively correlated with the emotions of safe, lively, feminine, warm, and soft, while curvature was negatively correlated with the emotions of dangerous, rigorous, masculine, cold, and hard. In Study 2, one-way analysis of variance studied the influence of the proportion of length to width of human-machine interface on emotional preference. The results showed that the proportion affected Safe - Dangerous, Rigorous - Lively, Masculine - Feminine, and Cold - Warm, but not Soft - Hard. In Study 3, a two-way analysis of variance was conducted with Serious - Relaxed as target emotions, and the curvature and proportion were changed at the same time. The results showed no interaction between curvature and proportion, and people’s perception of curvature change was stronger than proportion. Therefore, designers should pay more attention to curvature design than the proportion of length to width of human-machine interface, and use curvature design to meet the consumers’ emotional needs, to increase aesthetic pleasure.

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References

  1. Adolphs R (2008) Fear, faces, and the human amygdala.CURR. Opin Neurobiol 18(2):166–172

    Article  Google Scholar 

  2. Akhtaruzzaman M, Shafie AA (2011) Geometrical substantiation of phi, the golden ratio and the baroque of nature, architecture, design and engineering.International. J Arts 1(1):1–22

    Google Scholar 

  3. Al-Samarraie H, Sarsam SM, Alzahrani AI, Alalwan N (2018) Personality and individual differences: the potential of using preferences for visual stimuli to predict the big five traits.Cognition. Technol Work 20:337–349

    Article  Google Scholar 

  4. Bar M, Neta M (2006) Humans prefer curved visual objects.Psychological. Science 17(8):645–648

    Google Scholar 

  5. Bar M, Neta M (2007) Visual elements of subjective preference modulate amygdala activation. Neuropsychologia 45(10):2191–2200

    Article  Google Scholar 

  6. Berlyne DE (1970) Novelty, complexity, and hedonic value.ATTEN. Percept Psycho 8(5):279–286

    Article  Google Scholar 

  7. Berlyne DE(1974) Studies in the new experimental aesthetics: Steps toward an objective psychology of aesthetic appreciation (Vol.Hemisphere Publishing Corporation, Washington, DC

  8. Blijlevens J, Creusen MEH, Schoormans JPL (2009) How consumers perceive product appearance: the identification of three product appearance attributes.International. J Design 3(3):27–35

    Google Scholar 

  9. Blijlevens J, Carbon CC, Mugge R, Schoormans JPL (2012) Aesthetic appraisal of product designs: independent effects of typicality and arousal.BRIT. J Psychol 103(1):44–57

    Google Scholar 

  10. Blijlevens J, Mugge R, Ye P, Schoormans JPL (2013) The influence of product exposure on trendiness and aesthetic appraisal.INT. J Des 7(1):55–67

    Google Scholar 

  11. Blijlevens J, Thurgood C, Hekkert P, Chen L, Leder H, Allan WTW (2017) The aesthetic pleasure in design scale: the development of a scale to measure aesthetic pleasure for designed artifacts.Psychology of. Aesthetics Creativity Arts 11(1):86–98

    Article  Google Scholar 

  12. Bloch P, Brunel FF, Arnold T (2003) Individual differences in the centrality of visual product aesthetics: concept and measurement. J Consum Res 29(4):551–565

    Article  Google Scholar 

  13. Chuang M, Ma Y (2001) Expressing the expected product images in product design of micro-electronic products. Int J Ind Ergon 27(4):233–245

    Article  Google Scholar 

  14. Deng L, Wang G (2020) Quantitative evaluation of visual aesthetics of human-machine interaction interface layout. Comput Intel Neurosc 6:1–14

    Google Scholar 

  15. Elam K (2001) Geometry of design: studies in proportion and composition. Princeton Architectural Press, New York

    Google Scholar 

  16. Hekkert P (2006) Design aesthetics: principles of pleasure in design. Psychol Sci 48(2):157–172

    Google Scholar 

  17. Hekkert P, Snelders D, van Wieringen PCW (2003) Most advanced, yet acceptable': Typicality and novelty as joint predictors of aesthetic preference in industrial design. Brit J Psychol 94(Pt 1):111–124

    Article  Google Scholar 

  18. Ho C, Lu Y, Chen C (2016) Influence of curvature and expertise on aesthetic preferences for mobile device designs. Int J Des 10(3):17–25

    Google Scholar 

  19. Hsiao K, Chen L (2006) Fundamental dimensions of affective responses to product shapes. Int J Ind Ergon 36(6):553–564

    Article  Google Scholar 

  20. Hsu SH, Chuang MC, Chang CC (2000) A semantic differential study of designers' and users' product form perception. Int J Industrial Ergon 25(4):375–391

    Article  Google Scholar 

  21. Hu M, Guo F, Duffy VG, Ren Z, Yue P (2020) Constructing and measuring domain-specific emotions for affective design: a descriptive approach to deal with individual differences. Ergonomics 63(5):563–578

    Article  Google Scholar 

  22. Huang D, Cui T (2014) Study of product shape correction method based on golden ratio. J Mach Design 31(9):120–122

    Google Scholar 

  23. Hung W, Chen L (2012) Effects of novelty and its dimensions on aesthetic preference in product design. Int J Des 6(2):81–90

    Google Scholar 

  24. Jung JY, Badke-Schaub P (2017) The impact of aesthetic preference in product design-golden ratio and. Korean’s Pref Proport 30(4):5–14

    Google Scholar 

  25. Kapkın E, Joines S (2018) An investigation into the relationship between product form and perceived meanings. Int J Ind Ergonom 67:259–273

    Article  Google Scholar 

  26. Karana E, van Weelderen W, van Woerden E. (2007). The effect of form on attributing meanings to materials. Paper presented at the Proceedings of the ASME 2007 International Design Engineering Technical Conferences & Computers and information in engineering conference, Las Vegas, Nevada, USA

  27. Kim W, Ko T, Rhiu I, Yun MH (2019) Mining affective experience for a kansei design study on a recliner. Appl Ergon 74:145–153

    Article  Google Scholar 

  28. Krippendorff K, Butter R (1984) Product semantics: exploring the symbolic qualities of form. Innovation 3(2):4–9

    Google Scholar 

  29. Leder H, Carbon C (2005) Dimensions in appreciation of car interior design. Appl Cognitive Psych 19(5):603–618

    Article  Google Scholar 

  30. Leder H, Tinio PPL, Bar M (2011) Emotional valence modulates the preference for curved objects. Perception 40(6):649–655

    Article  Google Scholar 

  31. Liu CH (1997) Symbols: circles and spheres represent the same referents. Metaphor Symbol 12(2):135–147

    Article  Google Scholar 

  32. Mariëlle EHC, Schoormans JPL (2005) The different roles of product appearance in consumer choice. J Prod Innovat Manag 22(1):63–81

    Article  Google Scholar 

  33. Mohanty SN, Suar D (2013) Decision-making in positive and negative prospects: influence of certainty and affectivity. Int J Adv Psychol 2(1):19–28

    Google Scholar 

  34. Mohanty SN, Suar D (2014) Decision making under uncertainty and information processing in positive and negative mood states. Psychol Rep 115(1):91–105

    Article  Google Scholar 

  35. Moshagen M, Thielsch MT (2010) Facets of visual aesthetics. Int J Human-Comput Stud 68(10):689–709

    Article  Google Scholar 

  36. Mugge R, Govers PCM, Schoormans JPL (2009) The development and testing of a product personality scale. Design Stud 30(3):287–302

    Article  Google Scholar 

  37. Murray EA (2007) The amygdala, reward and emotion. Trends Cogn Sci 11(11):489–497

    Article  Google Scholar 

  38. Ngo DCL, Teo LS, Byrne JG (2003) Modelling interface aesthetics. Inform Sci 152:25–46

    Article  Google Scholar 

  39. Norman DA(2004) Why we love (or hate) everyday things (Vol. Basic Books,New York

  40. Shang M (2009) Application of proportionality factor in product shape design. Pack Eng 30(8):135–137

    Google Scholar 

  41. Sieu B, Gavrilova M (2020) Biometric identification from human aesthetic preferences. Sensors-Basel 20(4):1–19

    Article  Google Scholar 

  42. Silvera DH, Josephs RA, Giesler RB (2002) Bigger is better: the influence of physical size on aesthetic preference judgments. J Behav Decis Making 15(3):189–202

    Article  Google Scholar 

  43. Silvia PJ, Barona CM (2009) Do people prefer curved objects? Angularity, expertise, and aesthetic preference. Empir Stud Arts 27(1):25–42

    Article  Google Scholar 

  44. Strohmeier P, Carrascal JP, Cheng B, Meban M, Vertegaal R (2016). An evaluation of shape changes for conveying emotions. Paper presented at the Proceedings of the 2016 CHI conference on human factors in computing systems, San Jose, CA, USA

  45. Troncoso XG, Macknik SL, Martinez-Conde S (2010) Corner salience varies parametrically with corner angle during flicker-augmented contrast. J Vision 6(6):717

    Article  Google Scholar 

  46. Velasco C, Woods AT, Petit O, Cheok AD, Spence C (2016) Crossmodal correspondences between taste and shape, and their implications for product packaging: a review. Food Qual Prefer 52:17–26

    Article  Google Scholar 

  47. Veryzer RWJ, Hutchinson JW (1998) The influence of unity and prototypicality on aesthetic responses to new product designs. J Consum Res 24(4):374–394

    Article  Google Scholar 

  48. Wang Y, Yang S, Xu A, Wang R (2017) Detail form design of product. Pack Eng 38(24):216–222

    Google Scholar 

  49. Westerman SJ, Gardner PH, Sutherland EJ, White T, Jordan K, Watts D, Wells S (2012) Product design: preference for rounded versus angular design elements. Psychol Mark 29(8):595–605

    Article  Google Scholar 

  50. Westerman SJ, Sutherland EJ, Gardner PH, Baig N, Critchley C, Hickey C, Mehigan S, Solway A, Zervos Z (2013) The design of consumer packaging: effects of manipulations of shape, orientation, and alignment of graphical forms on consumers' assessments. Food Qual Prefer 27(1):8–17

    Article  Google Scholar 

  51. Xue W (ed) (2013) In: Statistical analysis and SPSS application. China Renmin University Press, Beijing

  52. You H, Chen K (2007) Applications of affordance and semantics in product design. Design Stud 28(1):23–38

    Article  Google Scholar 

  53. Zhou L, Xue C, Tang W, Li J, Niu Y (2013) Aesthetic evaluation method of interface elements layout design. J Comput-Aided Design Comput Graphics 25(5):758–766

    Google Scholar 

  54. Zhu L, Li Y (2010) Shape proportion of Banpo pottery and the revelation on modern product design. Packaging Eng 31(24):51–54

    Google Scholar 

Download references

Funding

This project is supported by National Natural Science Foundation of China (Grant No. 51905458); Open Research Subject of Research Center of Industrial Design (Grant No. GYSJ2019–003) and Sub-project of National Key Research and Development Program (Grant No. 2018YFC0310201–08).

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Correspondence to Li Deng.

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Deng, L. The influence of curvature and proportion on emotional preference for human-machine interface design. Multimed Tools Appl 81, 43581–43611 (2022). https://doi.org/10.1007/s11042-022-12835-x

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