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Extending the Spectrum of Dysgraphia: A Data Driven Strategy to Estimate Handwriting Quality

This paper proposes new ways to assess handwriting, a critical skill in any child’s school journey. Traditionally, a pen and paper test called the BHK test (Concise Evaluation Scale for Children’s Handwriting) is used to assess children’s handwriting in French-speaking countries. Any child with a BH...

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Autores principales: Asselborn, Thibault, Chapatte, Mateo, Dillenbourg, Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7035284/
https://www.ncbi.nlm.nih.gov/pubmed/32081940
http://dx.doi.org/10.1038/s41598-020-60011-8
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author Asselborn, Thibault
Chapatte, Mateo
Dillenbourg, Pierre
author_facet Asselborn, Thibault
Chapatte, Mateo
Dillenbourg, Pierre
author_sort Asselborn, Thibault
collection PubMed
description This paper proposes new ways to assess handwriting, a critical skill in any child’s school journey. Traditionally, a pen and paper test called the BHK test (Concise Evaluation Scale for Children’s Handwriting) is used to assess children’s handwriting in French-speaking countries. Any child with a BHK score above a certain threshold is diagnosed as ‘dysgraphic’, meaning that they are then eligible for financial coverage for therapeutic support. We previously developed a version of the BHK for tablet computers which provides rich data on the dynamics of writing (acceleration, pressure, and so forth). The underlying model was trained on dysgraphic and non-dysgraphic children. In this contribution, we deviate from the original BHK for three reasons. First, in this instance, we are interested not in a binary output but rather a scale of handwriting difficulties, from the lightest cases to the most severe. Therefore, we wish to compute how far a child’s score is from the average score of children of the same age and gender. Second, our model analyses dynamic features that are not accessible on paper; hence, the BHK is useful in this instance. Using the PCA (Principal Component Analysis) reduced the set of 53 handwriting features to three dimensions that are independent of the BHK. Nonetheless, we double-checked that, when clustering our data set along any of these three axes, we accurately detected dysgraphic children. Third, dysgraphia is an umbrella concept that embraces a broad variety of handwriting difficulties. Two children with the same global score can have totally different types of handwriting difficulties. For instance, one child could apply uneven pen pressure while another one could have trouble controlling their writing speed. Our new test not only provides a global score, but it also includes four specific score for kinematics, pressure, pen tilt and static features (letter shape). Replacing a global score with a more detailed profile enables the selection of remediation games that are very specific to each profile.
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spelling pubmed-70352842020-02-28 Extending the Spectrum of Dysgraphia: A Data Driven Strategy to Estimate Handwriting Quality Asselborn, Thibault Chapatte, Mateo Dillenbourg, Pierre Sci Rep Article This paper proposes new ways to assess handwriting, a critical skill in any child’s school journey. Traditionally, a pen and paper test called the BHK test (Concise Evaluation Scale for Children’s Handwriting) is used to assess children’s handwriting in French-speaking countries. Any child with a BHK score above a certain threshold is diagnosed as ‘dysgraphic’, meaning that they are then eligible for financial coverage for therapeutic support. We previously developed a version of the BHK for tablet computers which provides rich data on the dynamics of writing (acceleration, pressure, and so forth). The underlying model was trained on dysgraphic and non-dysgraphic children. In this contribution, we deviate from the original BHK for three reasons. First, in this instance, we are interested not in a binary output but rather a scale of handwriting difficulties, from the lightest cases to the most severe. Therefore, we wish to compute how far a child’s score is from the average score of children of the same age and gender. Second, our model analyses dynamic features that are not accessible on paper; hence, the BHK is useful in this instance. Using the PCA (Principal Component Analysis) reduced the set of 53 handwriting features to three dimensions that are independent of the BHK. Nonetheless, we double-checked that, when clustering our data set along any of these three axes, we accurately detected dysgraphic children. Third, dysgraphia is an umbrella concept that embraces a broad variety of handwriting difficulties. Two children with the same global score can have totally different types of handwriting difficulties. For instance, one child could apply uneven pen pressure while another one could have trouble controlling their writing speed. Our new test not only provides a global score, but it also includes four specific score for kinematics, pressure, pen tilt and static features (letter shape). Replacing a global score with a more detailed profile enables the selection of remediation games that are very specific to each profile. Nature Publishing Group UK 2020-02-21 /pmc/articles/PMC7035284/ /pubmed/32081940 http://dx.doi.org/10.1038/s41598-020-60011-8 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Asselborn, Thibault
Chapatte, Mateo
Dillenbourg, Pierre
Extending the Spectrum of Dysgraphia: A Data Driven Strategy to Estimate Handwriting Quality
title Extending the Spectrum of Dysgraphia: A Data Driven Strategy to Estimate Handwriting Quality
title_full Extending the Spectrum of Dysgraphia: A Data Driven Strategy to Estimate Handwriting Quality
title_fullStr Extending the Spectrum of Dysgraphia: A Data Driven Strategy to Estimate Handwriting Quality
title_full_unstemmed Extending the Spectrum of Dysgraphia: A Data Driven Strategy to Estimate Handwriting Quality
title_short Extending the Spectrum of Dysgraphia: A Data Driven Strategy to Estimate Handwriting Quality
title_sort extending the spectrum of dysgraphia: a data driven strategy to estimate handwriting quality
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7035284/
https://www.ncbi.nlm.nih.gov/pubmed/32081940
http://dx.doi.org/10.1038/s41598-020-60011-8
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