Developmental Dysgraphia Diagnosis Based On Quantitative Analysis Of Online Handwriting
Abstract
The prevalence of handwriting difficulties among school-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.
Keywords
developmental dysgraphia, digitizing tablet, online handwriting, quantitative analysis, diagnosisPersistent identifier
http://hdl.handle.net/11012/138274Document type
Peer reviewedDocument version
Final PDFSource
Proceedings of the 24th Conference STUDENT EEICT 2018. s. 446-450. ISBN 978-80-214-5614-3http://www.feec.vutbr.cz/EEICT/
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- Student EEICT 2018 [157]