Physiological responses related to visual impressions of a product

Evaluating automobile interior design

Hidemaru Muto, Tsuneyuki Yamamoto, Naoki Kamiya, Miwa Nakanishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In many products, the visual impressions of the product are extremely important components—sight accounts for 83 % of the five senses (An education apparatus editing committee in An industrial education apparatus system manual. JUS Press 1972). However, manufacturers still depend on the aspect of the effectiveness, efficiency, and usability for the design evaluation of products; yet, consumer emotion is hard to measure because the mental side of users such as visual impressions cannot be observed directly and the index to measure them has not been established. The function, performance, and usability can be measured by the behavioral index of users (e.g., operation time and error rate) (Nagashima and Kubo in The sensitivity and information for the new manufacturing. Morikita Shuppan Co., Ltd, 2007). In this study, we experimentally searched for indices to objectively detect the impression of appearance with car images as targets. We observed that MPFC activation is related to high “familiarity” and low “mechanical” features.

Original languageEnglish
Title of host publicationAdvances in Ergonomics Modeling, Usability
PublisherSpringer Verlag
Pages621-633
Number of pages13
Volume486
ISBN (Print)9783319416847
DOIs
Publication statusPublished - 2017
EventInternational Conference on Ergonomics Modeling, Usability and Special Populations, AHFE 2016 - Walt Disney World, United States
Duration: 2016 Jul 272016 Jul 31

Publication series

NameAdvances in Intelligent Systems and Computing
Volume486
ISSN (Print)21945357

Other

OtherInternational Conference on Ergonomics Modeling, Usability and Special Populations, AHFE 2016
CountryUnited States
CityWalt Disney World
Period16/7/2716/7/31

Fingerprint

Automobiles
Education
Railroad cars
Chemical activation

Keywords

  • Car appearance
  • Physiological responses
  • Subjectivity evaluation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Muto, H., Yamamoto, T., Kamiya, N., & Nakanishi, M. (2017). Physiological responses related to visual impressions of a product: Evaluating automobile interior design. In Advances in Ergonomics Modeling, Usability (Vol. 486, pp. 621-633). (Advances in Intelligent Systems and Computing; Vol. 486). Springer Verlag. https://doi.org/10.1007/978-3-319-41685-4_55

Physiological responses related to visual impressions of a product : Evaluating automobile interior design. / Muto, Hidemaru; Yamamoto, Tsuneyuki; Kamiya, Naoki; Nakanishi, Miwa.

Advances in Ergonomics Modeling, Usability. Vol. 486 Springer Verlag, 2017. p. 621-633 (Advances in Intelligent Systems and Computing; Vol. 486).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Muto, H, Yamamoto, T, Kamiya, N & Nakanishi, M 2017, Physiological responses related to visual impressions of a product: Evaluating automobile interior design. in Advances in Ergonomics Modeling, Usability. vol. 486, Advances in Intelligent Systems and Computing, vol. 486, Springer Verlag, pp. 621-633, International Conference on Ergonomics Modeling, Usability and Special Populations, AHFE 2016, Walt Disney World, United States, 16/7/27. https://doi.org/10.1007/978-3-319-41685-4_55
Muto H, Yamamoto T, Kamiya N, Nakanishi M. Physiological responses related to visual impressions of a product: Evaluating automobile interior design. In Advances in Ergonomics Modeling, Usability. Vol. 486. Springer Verlag. 2017. p. 621-633. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-319-41685-4_55
Muto, Hidemaru ; Yamamoto, Tsuneyuki ; Kamiya, Naoki ; Nakanishi, Miwa. / Physiological responses related to visual impressions of a product : Evaluating automobile interior design. Advances in Ergonomics Modeling, Usability. Vol. 486 Springer Verlag, 2017. pp. 621-633 (Advances in Intelligent Systems and Computing).
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