D 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

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
Název: Výzkum pokročilých metod diagnózy a hodnocení vývojové dysgrafie založených na kvantitativní analýze online písma a kresby (Akronym: DiagnosisDysgraphia)
Investor: Grantová agentura ČR, Výzkum pokročilých metod diagnózy a hodnocení vývojové dysgrafie založených na kvantitativní analýze online písma a kresby