Exploring the Contribution of Isochrony-based Features to
Computerized Assessment of Handwriting Disabilities

D 2022

Exploring the Contribution of Isochrony-based Features to Computerized Assessment of Handwriting Disabilities

GAVENČIAK, Michal, Vojtěch ZVONČÁK, Jiří MEKYSKA, Katarína ŠAFÁROVÁ, Lukáš ČUNEK et. al.

Basic information

Original name

Exploring the Contribution of Isochrony-based Features to Computerized Assessment of Handwriting Disabilities

Authors

GAVENČIAK, Michal (203 Czech Republic), Vojtěch ZVONČÁK (203 Czech Republic), Jiří MEKYSKA (203 Czech Republic), Katarína ŠAFÁROVÁ (203 Czech Republic, guarantor, belonging to the institution), Lukáš ČUNEK (203 Czech Republic, belonging to the institution), Tomáš URBÁNEK (203 Czech Republic, belonging to the institution), Jana Marie HAVIGEROVÁ (203 Czech Republic, belonging to the institution), Jiřina BEDNÁŘOVÁ (203 Czech Republic), Zoltán GALÁŽ (703 Slovakia) and Ján MUCHA (703 Slovakia)

Edition

Praha, 45th International Conference on Telecommunications and Signal Processing (TSP), p. 355-359, 5 pp. 2022

Publisher

Institute of Electrical and Electronics Engineers

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

50102 Psychology, special ;

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

URL

RIV identification code

RIV/00216224:14210/22:00129226

Organization unit

Faculty of Arts

ISBN

978-1-6654-6948-7

DOI

http://dx.doi.org/10.1109/TSP55681.2022.9851254

UT WoS

001070846300072

Keywords in English

Analytical models; Estimation error; Databases; Computational modeling; Machine learning; Signal processing; Predictive models

Abstract

V originále

Approximately 30–60 % of the time children spend in school is associated with handwriting. However, up to 30 % of them experience handwriting disabilities (HD), which lead to a decrease in their academic performance. Current HD assessment methods are not unified and show signs of subjectivity which can lead to misdiagnosis. The aim of this paper is to propose a new approach to objective HD assessment based on the principle of movement isochrony. For this purpose, we used a database of 137 children attending a primary school, who performed a transcription and dictation task, and who were associated with a BHK (Concise Evaluation Scale for Children's Handwriting) score. Employing a machine learning model, we were able to estimate this score with 18 % error. An interpretation of the model suggests that the isochrony-based features could bring new benefits to the objective assessment of HD.

Links

GA18-16835S, research and development project

Name: Výzkum pokročilých metod diagnózy a hodnocení vývojové dysgrafie založených na kvantitativní analýze online písma a kresby (Acronym: DiagnosisDysgraphia)

Investor: Czech Science Foundation

Citovat

GAVENČIAK, Michal, Vojtěch ZVONČÁK, Jiří MEKYSKA, Katarína ŠAFÁROVÁ, Lukáš ČUNEK, Tomáš URBÁNEK, Jana Marie HAVIGEROVÁ, Jiřina BEDNÁŘOVÁ, Zoltán GALÁŽ and Ján MUCHA. Exploring the Contribution of Isochrony-based Features to Computerized Assessment of Handwriting Disabilities. Online. In Herencsar, Norbert. 45th International Conference on Telecommunications and Signal Processing (TSP). Praha: Institute of Electrical and Electronics Engineers, 2022, p. 355-359. ISBN 978-1-6654-6948-7. Available from: https://dx.doi.org/10.1109/TSP55681.2022.9851254.

@inproceedings{2233767,
   author = {Gavenčiak, Michal and Zvončák, Vojtěch and Mekyska, Jiří and Šafárová, Katarína and Čunek, Lukáš and Urbánek, Tomáš and Havigerová, Jana Marie and Bednářová, Jiřina and Galáž, Zoltán and Mucha, Ján},
   address = {Praha},
   booktitle = {45th International Conference on Telecommunications and Signal Processing (TSP)},
   doi = {http://dx.doi.org/10.1109/TSP55681.2022.9851254},
   editor = {Herencsar, Norbert},
   keywords = {Analytical models; Estimation error; Databases; Computational modeling; Machine learning; Signal processing; Predictive models},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Praha},
   isbn = {978-1-6654-6948-7},
   pages = {355-359},
   publisher = {Institute of Electrical and Electronics Engineers},
   title = {Exploring the Contribution of Isochrony-based Features to Computerized Assessment of Handwriting Disabilities},
   url = {https://ieeexplore.ieee.org/document/9851254},
   year = {2022}
}

TY  - JOUR
ID  - 2233767
AU  - Gavenčiak, Michal - Zvončák, Vojtěch - Mekyska, Jiří - Šafárová, Katarína - Čunek, Lukáš - Urbánek, Tomáš - Havigerová, Jana Marie - Bednářová, Jiřina - Galáž, Zoltán - Mucha, Ján
PY  - 2022
TI  - Exploring the Contribution of Isochrony-based Features to Computerized Assessment of Handwriting Disabilities
PB  - Institute of Electrical and Electronics Engineers
CY  - Praha
SN  - 9781665469487
KW  - Analytical models
KW  - Estimation error
KW  - Databases
KW  - Computational modeling
KW  - Machine learning
KW  - Signal processing
KW  - Predictive models
UR  - https://ieeexplore.ieee.org/document/9851254
N2  - Approximately 30–60 % of the time children spend in school is associated with handwriting. However, up to 30 % of them experience handwriting disabilities (HD), which lead to a decrease in their academic performance. Current HD assessment methods are not unified and show signs of subjectivity which can lead to misdiagnosis. The aim of this paper is to propose a new approach to objective HD assessment based on the principle of movement isochrony. For this purpose, we used a database of 137 children attending a primary school, who performed a transcription and dictation task, and who were associated with a BHK (Concise Evaluation Scale for Children's Handwriting) score. Employing a machine learning model, we were able to estimate this score with 18 % error. An interpretation of the model suggests that the isochrony-based features could bring new benefits to the objective assessment of HD.
ER  -

GAVENČIAK, Michal, Vojtěch ZVONČÁK, Jiří MEKYSKA, Katarína ŠAFÁROVÁ, Lukáš ČUNEK, Tomáš URBÁNEK, Jana Marie HAVIGEROVÁ, Jiřina BEDNÁŘOVÁ, Zoltán GALÁŽ and Ján MUCHA. Exploring the Contribution of Isochrony-based Features to Computerized Assessment of Handwriting Disabilities. Online. In Herencsar, Norbert. \textit{45th International Conference on Telecommunications and Signal Processing (TSP)}. Praha: Institute of Electrical and Electronics Engineers, 2022, p.~355-359. ISBN~978-1-6654-6948-7. Available from: https://dx.doi.org/10.1109/TSP55681.2022.9851254.

Detailed Information on Publication Record