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@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.
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