Identification and Rating of Developmental Dysgraphia by Handwriting Analysis

Jiri Mekyska, Marcos Faundez-Zanuy, Zdenek Mzourek, Zoltan Galaz, Zdenek Smekal, Sara Rosenblum

Research output: Contribution to journalArticlepeer-review


Developmental dysgraphia, being observed among 10-30% of school-aged children, is a disturbance or difficulty in the production of written language that has to do with the mechanics of writing. The objective of this study is to propose a method that can be used for automated diagnosis of this disorder, as well as for estimation of difficulty level as determined by the handwriting proficiency screening questionnaire. We used a digitizing tablet to acquire handwriting and consequently employed a complex parameterization in order to quantify its kinematic aspects and hidden complexities. We also introduced a simple intrawriter normalization that increased dysgraphia discrimination and HPSQ estimation accuracies. Using a random forest classifier, we reached 96% sensitivity and specificity, while in the case of automated rating by the HPSQ total score, we reached 10% estimation error. This study proves that digital parameterization of pressure and altitude/tilt patterns in children with dysgraphia can be used for preliminary diagnosis of this writing disorder.

Original languageEnglish
Article number7530869
Pages (from-to)235-248
Number of pages14
JournalIEEE Transactions on Human-Machine Systems
Issue number2
StatePublished - Apr 2017

Bibliographical note

Publisher Copyright:
© 2016 IEEE.


  • Dysgraphia
  • handwriting analysis
  • handwriting proficiency screening questionnaire (HPSQ)
  • intrawriter normalization
  • rating

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Control and Systems Engineering
  • Signal Processing
  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence


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