2019
Fractional Order Derivatives Evaluation in Computerized Assessment of Handwriting Difficulties in School-aged Children
ZVONČÁK, Vojtěch; Jan MUCHA; Zoltan GALÁŽ; Jiří MEKYSKA; Katarína ŠAFÁROVÁ et al.Základní údaje
Originální název
Fractional Order Derivatives Evaluation in Computerized Assessment of Handwriting Difficulties in School-aged Children
Autoři
ZVONČÁK, Vojtěch; Jan MUCHA; Zoltan GALÁŽ; Jiří MEKYSKA; Katarína ŠAFÁROVÁ; Marcos FAUNDEZ-ZANUY a Zdeněk SMÉKAL
Vydání
Dublin, 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), od s. 210-215, 6 s. 2019
Nakladatel
IEEE
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
50102 Psychology, special
Stát vydavatele
Irsko
Utajení
není předmětem státního či obchodního tajemství
Forma vydání
elektronická verze "online"
Označené pro přenos do RIV
Ano
Kód RIV
RIV/00216224:14210/19:00107994
Organizační jednotka
Filozofická fakulta
ISBN
978-1-7281-5763-4
ISSN
UT WoS
EID Scopus
Klíčová slova anglicky
fractal calculus; fractional derivative; handwriting difficulties; kinematic analysis; online handwriting; school-aged children; digitizer; developmental dysgraphia
Štítky
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 27. 6. 2024 10:34, Mgr. Michal Petr
Anotace
V originále
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.
Návaznosti
| GA18-16835S, projekt VaV |
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