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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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • 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

  • e-ISSN

  • 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