New Approach of Dysgraphic Handwriting Analysis Based on the Tunable Q-Factor Wavelet Transform
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU132674" target="_blank" >RIV/00216305:26220/19:PU132674 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8756872/" target="_blank" >https://ieeexplore.ieee.org/document/8756872/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.23919/MIPRO.2019.8756872" target="_blank" >10.23919/MIPRO.2019.8756872</a>
Alternative languages
Result language
angličtina
Original language name
New Approach of Dysgraphic Handwriting Analysis Based on the Tunable Q-Factor Wavelet Transform
Original language description
Developmental dysgraphia is a neurodevelopmental disorder present in up to 30% of elementary school pupils. Since it is associated with handwriting difficulties (HD), it has detrimental impact on children’s academic progress, emotional well-being, attitude and behaviour. Nowadays, researchers proposed a new approach of HD assessment utilizing digitizing tablets. I.e. that handwriting of children is quantified by a set of conventional parameters, such as velocity, duration of handwriting, tilt, etc. The aim of this study is to explore a potential of newly designed online handwriting features based on the tunable Q-factor wavelet transform (TQWT) in terms of computerized HD identification. Using a digitizing tablet, we recorded a written paragraph of 97 children who were also assessed by the Handwriting Proficiency Screening Questionnaire for Children (HPSQ–C). We evaluated discrimination power (binary classification) of all parameters using random forest and support vector machine classifiers in combination with sequential floating forward feature selection. Based on the experimental results we observed that the newly designed features outperformed the conventional ones (accuracy = 79.16%, sensitivity = 86.22%, specificity = 73.32%). When considering the combination of all parameters (including the conventional ones) we reached 84.66% classification accuracy (sensitivity = 88.70%, specificity = 82.53%). The most discriminative parameters were based on vertical movement and pressure, which suggests that children with HD were not able to maintain stable force on pen tip and that their vertical movement is less fluent. The new features we introduced go beyond the state-of-the-art and improve discrimination power of the conventional parameters by approximately 20.0%.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)
ISBN
978-953-233-098-4
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
289-294
Publisher name
Neuveden
Place of publication
Opatja, Chorvatsko
Event location
Opatija
Event date
Mar 20, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000484544500055