Fractional Order Derivatives Evaluation in Computerized Assessment of Handwriting Difficulties in School-aged Children
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU133984" target="_blank" >RIV/00216305:26220/19:PU133984 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8970811" target="_blank" >https://ieeexplore.ieee.org/document/8970811</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICUMT48472.2019.8970811" target="_blank" >10.1109/ICUMT48472.2019.8970811</a>
Alternative languages
Result language
angličtina
Original language name
Fractional Order Derivatives Evaluation in Computerized Assessment of Handwriting Difficulties in School-aged Children
Original language description
Handwriting difficulties (HD) affects some of the school-aged children and its current prevalence rate is between 5-34%. Children at primary schools have to face rising cognitive demands that the handwriting represents, and some of them are not able to do so. As a result, they tend to make mistakes and their written product is dysfluent and has poor legibility. HD can also lead them to lower self-esteem, learning difficulties and ultimately to less academic achievements. For this reason occupational therapists are trying to identify HD through examination as early as possible. We extracted online handwriting signals of children using digitizing tablets. Handwriting Proficiency Screening Questionnaire for Children (HPSQ-C) was used to score severity of HD in children's written product. To advance current computerized analysis of online handwriting, we employed fractional order derivatives features (FD) together with conventional features. We selected the significant features for HD identification and utilize correlation analysis together with Mann-Whitney U-test to evaluate their discrimination power. We can conclude that FD-based features bring benefits of more robust quantification of in-air movements as opposed to the conventionally used ones. Finally, we have shown that utilization of FD can be beneficial for computerized assessment of HD but should be further optimized and evaluated with advanced statistical or machine learning methods.
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
11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)
ISBN
978-1-7281-5764-1
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
210-215
Publisher name
Neuveden
Place of publication
neuveden
Event location
Dublin
Event date
Oct 28, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000540651700027