Skip to main content
SpringerLink
Log in

Evaluation of handwriting task difficulty based on detrended fluctuation analysis

  • Original Article
  • Published:
Artificial Life and Robotics Aims and scope Submit manuscript

Abstract

The control of voluntary movements is a dual structure consisting of cognitive and physical controls; cognitive control involves attentional resources, unlike physical control. Various voluntary movements can be performed by combining cognitive and physical controls. Body movements depending on attentional resources are performed using cognitive control; these movements fluctuate with white noise and their fluctuations gradually become the one-over-f fluctuation as the dependence on the attentional resources decreases. The handwriting process of characters is a voluntary movement. This study focused on the relationship between the repetitive handwriting process and the attentional resources allocated to it. The attention resources allocated to the handwriting process depend on the difficulty of the handwriting task. Moreover, the difficulty of a handwriting task is determined by the complexity of the shape of the handwritten characters, and the stroke counts is one indicator of this. Therefore, we focused on five Chinese kanji characters with different stroke counts. We investigated fluctuations in the temporal and spatial handwriting elements (twelve handwriting elements in all) defined within the handwriting process of each Chinese kanji character. The detrended fluctuation analysis was applied to the fluctuation analysis of the handwriting elements. In this paper, we discussed the relationship between the handwriting task difficulties and handwriting elements using local scaling indices based on the detrended fluctuation analysis.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Miyake Y, Onishi Y, Pppel E (2007) Two types of anticipatory-timing mechanism in synchronization tapping. In: Object recognition, attention, and action. Springer, Berlin, pp 231–244

  2. Komatsu T, Miyake Y (2005) Time evolution of asynchronous value in synchronization tapping task (in Japanese). SICE 41(6):518–526

    Google Scholar 

  3. Maleki A, Oshima Y, Nozawa A, Mizuno T, Uchida M (2015) Analysis of fluctuation in repeated handwriting based on psychophysiological factors. In: 7th International conference on unsolved problems on noise, p 21

  4. Kumagai R, Uchida M (2017) Detrended fluctuation analysis of repetitive handwriting. In: 2017 International conference on noise and fluctuations, pp 350–353

  5. Mandelbrot BB, Wallis JR (1969) Some long-run properties of geophysical records. Water Resour Res 5(2):321–340

    Article  Google Scholar 

  6. Hardstone R, Poil S-S, Schiavone G, Jansen R, Nikulin V, Mansvelder HD, Linkenkaer-Hansen K (2012) Detrended fluctuation analysis: a scale-free view on neuronal oscillations. Front Physiol 3(450):1–13

    Google Scholar 

  7. Peng CK, Havlin S, Stanley HE, Goldberger AL (1995) Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. CHAOS 5(1):82–87

    Article  Google Scholar 

  8. Bryce RM, Sprague KB (2012) Revisiting detrended fluctuation analysis. Sci Rep. https://doi.org/10.1038/srep00315

    Article  Google Scholar 

  9. Kumagai R, Uchida M (2018) Fluctuation analysis of synchronous repetitive handwriting. In: 8th International conference on unsolved problems on noise. Book of Abstracts UPoN, p 130

  10. Uchida M (2019) Fluctuation analysis of repetitive writing motion by using DFA. In: 2019 International conference on noise and fluctuations. ICNF Proceedings, pp 112–115

  11. Tanaka K, Arai K, Uchida M (2019) Evaluation of task difficulty based on fluctuation characteristics in writing task. Artif Life Robot 25:17–23. https://doi.org/10.1007/s10015-019-00570-w

    Article  Google Scholar 

  12. Curran SL, Andrykowski MA, Studts JL (1995) Short form of the profile of mood states (POMS-SF): psychometric information. Psychol Assess 7(1):80–83

    Article  Google Scholar 

  13. Spielberger Charles D, Gorsuch Richard L, Lushene Robert E (1970) STAI manual for the state-trait anxiety inventory (self-evaluation questionnaire). Consulting Psychologists Press, Mountain View

    Google Scholar 

Download references

Acknowledgements

This work was supported by JSPS KAKENHI Grant-in-Aid for Scientific Research (C) Number 17K00477. The authors would like to thank Enago (http://www.enago.jp) for the English language review.

Author information

Authors and Affiliations

  1. The Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo, Japan

    Keisuke Tanaka & Masafumi Uchida

Authors
  1. Keisuke Tanaka
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Masafumi Uchida
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Masafumi Uchida.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This work was presented in part at the 25th International Symposium on Artificial Life and Robotics (Beppu, Oita, January 22–24, 2020).

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tanaka, K., Uchida, M. Evaluation of handwriting task difficulty based on detrended fluctuation analysis. Artif Life Robotics 26, 169–175 (2021). https://doi.org/10.1007/s10015-020-00672-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10015-020-00672-w

Keywords

Search

Navigation