Detail publikačního výsledku

Developmental Dysgraphia Diagnosis Based on Quantitative Analysis of Online Handwriting

ZVONČÁK, V.

Originální název

Developmental Dysgraphia Diagnosis Based on Quantitative Analysis of Online Handwriting

Anglický název

Developmental Dysgraphia Diagnosis Based on Quantitative Analysis of Online Handwriting

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

The prevalence of handwriting difficulties amongs chool-aged children is around 10–30%. Until now, there is no objective method to diagnose and rate developmental dysgraphia (DD) in Czech Republic. The goal of this study is to propose a new method of objective DD diagnosis based on quantitative analysis of online handwriting. For this purpose, we extracted a set of spatial, temporal, kinematic and dynamic features from three handwriting tasks. Consequently, we performed a correlation analysis between these features and score of handwriting proficiency screening questionaire (HPSQ), in order to identify parameters with a good discrimination power. Using random forests classifier in combination with quantification of alphabet writing task, we reached nearly 77% classification accuracy (75% sensitivity, 80% specificity). This pilot study proves the possibility of automatic DD diagnosis in children cohort writing with cursive letters.

Anglický abstrakt

The prevalence of handwriting difficulties amongs chool-aged children is around 10–30%. Until now, there is no objective method to diagnose and rate developmental dysgraphia (DD) in Czech Republic. The goal of this study is to propose a new method of objective DD diagnosis based on quantitative analysis of online handwriting. For this purpose, we extracted a set of spatial, temporal, kinematic and dynamic features from three handwriting tasks. Consequently, we performed a correlation analysis between these features and score of handwriting proficiency screening questionaire (HPSQ), in order to identify parameters with a good discrimination power. Using random forests classifier in combination with quantification of alphabet writing task, we reached nearly 77% classification accuracy (75% sensitivity, 80% specificity). This pilot study proves the possibility of automatic DD diagnosis in children cohort writing with cursive letters.

Klíčová slova

developmental dysgraphia; digitizing tablet; online handwriting; quantitative analysis; diagnosis

Klíčová slova v angličtině

developmental dysgraphia; digitizing tablet; online handwriting; quantitative analysis; diagnosis

Autoři

ZVONČÁK, V.

Rok RIV

2019

Vydáno

26.04.2018

Místo

Brno

ISBN

978-80-214-5614-3

Kniha

Proceedings of the 24nd Conference STUDENT EEICT 2018

Strany od

446

Strany do

450

Strany počet

5

URL

http://www.feec.vutbr.cz/EEICT/archiv/sborniky/EEICT_2018_sbornik.pdf

BibTex

@inproceedings{BUT147385,
  author="Vojtěch {Zvončák}",
  title="Developmental Dysgraphia Diagnosis Based on Quantitative Analysis of Online Handwriting",
  booktitle="Proceedings of the 24nd Conference STUDENT EEICT 2018",
  year="2018",
  pages="446--450",
  address="Brno",
  isbn="978-80-214-5614-3",
  url="http://www.feec.vutbr.cz/EEICT/archiv/sborniky/EEICT_2018_sbornik.pdf"
}