Construction of Impression Estimation Models for the Design of Smartphone Vibration Feedback

  • Shota Shiraga
  • Yuichiro Kinoshita
  • Takashi Totsuka
  • Kentaro Go
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 739)


The importance of vibration feedback on mobile devices has been discussed in the human-computer interaction community. However, the psychological effects in the vibration feedback have not been much discussed. The goal of this study is to construct a design support system for vibration feedback, which considers user impressions. Toward constructing this system, a set of models to quantify the impressions is necessary as the first step. This paper describes the construction of the impression estimation models. We first quantified how the vibration feedback affects user impressions using the 85 various types of patterns. The result of the quantification revealed that users’ impressions can be controlled by changing the features of vibration patterns. On the basis of the results, we extracted three feature categories: intensity, suspension and change in intensity, and seven features in total were determined for these categories. Using the determined features and the quantification results, neural-network-based models were separately constructed for eight pairs of adjectives. The performance tests of the constructed models demonstrated sufficient accuracy. For all models, the average errors between the subjective evaluation and model output scores were within 7%. Also, all correlation coefficients between these scores showed a significant correlation.


vibration feedback impression estimation model neural network 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Alvina, J., Zhao, S., Perrault, S. T., Azh, M., Roumen, T., Fjeld, M.: OmniVib: towards cross-body spatiotemporal vibrotactile notifications for mobile phones. In Proceedings of the 2015 CHI Conference on Human Factors in Computing Systems, pp. 2487–2496 (2015).Google Scholar
  2. 2.
    Cauchard, J. R., Cheng, J. L., Pietrzak, T., Landay, J. A.: ActiVibe: design and evaluation of vibrations for progress monitoring. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pp. 3261–3271 (2016).Google Scholar
  3. 3.
    Saket, B., Parasojo, C., Huang, Y., Zhao, S.: Designing an effective vibration-based notification interface for mobile phones. In Proceedings of the 2013 Conference on Computer Supported Cooperative Work, pp. 1494–1504 (2013).Google Scholar
  4. 4.
    Nagamachi, M.: Kansei engineering as a powerful consumer-oriented technology for product development. Applied Ergonomics, Vol. 33, No. 3, pp. 289–294 (2002).Google Scholar
  5. 5.
    Barnes, C. J., Childs, T. H. C., Henson, B., Southee, C. H.: Surface finish and touch—a case study in a new human factors tribology. Wear, Vol. 257, No. 7–8, pp. 740–750 (2004).Google Scholar
  6. 6.
    Shiraga, S., Kinoshita, Y., Go, K.: Designing smartphone feedback based on vibration impression. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp. 3190–3196 (2016).Google Scholar
  7. 7.
    Philippa, M., Bove, V. M. Jr.: The EmotiveModeler: an emotive form design CAD tool. In Proceedings of the 2015 CHI Conference on Human Factors in Computing Systems, pp. 339–342 (2015).Google Scholar
  8. 8.
    Hsiao, S., Huang, H. C.: A neural network based approach for product form design. Design Studies, Vol. 23, No. 1, pp. 67–84 (2002).Google Scholar
  9. 9.
    Osgood, C. E., Suci, G. J., Tennenbaum, P. H.: The measurement of meaning. University of Illinois Press (1957).Google Scholar
  10. 10.
    Ward, J. H.: Hierarchical grouping to optimize an objective function. Journal of American Statistical Association, Vol. 58, No. 301, pp. 236–244 (1963).Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Shota Shiraga
    • 1
  • Yuichiro Kinoshita
    • 1
  • Takashi Totsuka
    • 1
  • Kentaro Go
    • 1
  1. 1.University of YamanashiKofuJapan

Personalised recommendations