Fractional Order Derivatives Evaluation in Computerized Assessment of Handwriting Difficulties in School-aged Children

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14210%2F19%3A00107994" target="_blank" >RIV/00216224:14210/19:00107994 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/ICUMT48472.2019.8970811" target="_blank" >http://dx.doi.org/10.1109/ICUMT48472.2019.8970811</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICUMT48472.2019.8970811" target="_blank" >10.1109/ICUMT48472.2019.8970811</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Fractional Order Derivatives Evaluation in Computerized Assessment of Handwriting Difficulties in School-aged Children

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Fractional Order Derivatives Evaluation in Computerized Assessment of Handwriting Difficulties in School-aged Children

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

50102 - Psychology, special (including therapy for learning, speech, hearing, visual and other physical and mental disabilities);

Projekt

<a href="/cs/project/GA18-16835S" target="_blank" >GA18-16835S: Výzkum pokročilých metod diagnózy a hodnocení vývojové dysgrafie založených na kvantitativní analýze online písma a kresby</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

ISBN

9781728157634

ISSN

2157-0221

e-ISSN

2157-023X

Počet stran výsledku

6

Strana od-do

210-215

Název nakladatele

IEEE

Místo vydání

Dublin

Místo konání akce

Dublin

Datum konání akce

1. 1. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000540651700027