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@article{1672124,
author = {Galáž, Zoltán and Mucha, Ján and Zvončák, Vojtěch and Mekyska, Jiří and Smékal, Zdeněk and Šafárová, Katarína and Ondráčková, Anežka and Urbánek, Tomáš and Havigerová, Jana Marie and Bednářová, Jiřina and FaundezandZanuy, Marcos},
article_location = {USA},
article_number = {June},
doi = {http://dx.doi.org/10.1109/ACCESS.2020.3003214},
keywords = {advanced parametrization; computerized analysis; graphomotor difficulties; machine learning; online handwriting},
language = {eng},
issn = {2169-3536},
journal = {IEEE Access},
title = {Advanced Parametrization of Graphomotor Difficulties in School-Aged Children},
url = {https://ieeexplore.ieee.org/abstract/document/9119411},
volume = {8},
year = {2020}
}
TY - JOUR
ID - 1672124
AU - Galáž, Zoltán - Mucha, Ján - Zvončák, Vojtěch - Mekyska, Jiří - Smékal, Zdeněk - Šafárová, Katarína - Ondráčková, Anežka - Urbánek, Tomáš - Havigerová, Jana Marie - Bednářová, Jiřina - Faundez-Zanuy, Marcos
PY - 2020
TI - Advanced Parametrization of Graphomotor Difficulties in School-Aged Children
JF - IEEE Access
VL - 8
IS - June
SP - 112883-112897
EP - 112883-112897
PB - IEEE Xplore Digital Library
SN - 21693536
KW - advanced parametrization
KW - computerized analysis
KW - graphomotor difficulties
KW - machine learning
KW - online handwriting
UR - https://ieeexplore.ieee.org/abstract/document/9119411
L2 - https://ieeexplore.ieee.org/abstract/document/9119411
N2 - School-aged children spend 31–60% of their time at school performing handwriting, which is a complex perceptual-motor skill composed of a coordinated combination of fine graphomotor movements. As up to 30% of them experience graphomotor difficulties (GD), timely diagnosis of these difficulties and therapeutic intervention are of great importance. At present, an objective, computerized decision support system for the identification and assessment of GD in school-aged children is still missing. In this study, we propose three novel advanced handwriting parametrization techniques based on modulation spectra, fractional order derivatives, and tunable Q-factor wavelet transform to improve the identification of GD using online handwriting. For this purpose, we analyzed signals acquired from 7 basic graphomotor tasks performed by 53 children attending 3rd and 4th grade at several primary schools around the Czech Republic. Combining the newly proposed features with the conventionally used ones, we were able to identify GD with 84% accuracy. In this study, we showed that using advanced parametrization of basic graphomotor movements can be potentially used to improve our capabilities of quantifying problems with the development of legible, fast-paced handwriting, and help with the early diagnosis of handwriting difficulties frequently manifested in developmental dysgraphia.
ER -
GALÁŽ, Zoltán, Ján MUCHA, Vojtěch ZVONČÁK, Jiří MEKYSKA, Zdeněk SMÉKAL, Katarína ŠAFÁROVÁ, Anežka ONDRÁČKOVÁ, Tomáš URBÁNEK, Jana Marie HAVIGEROVÁ, Jiřina BEDNÁŘOVÁ a Marcos FAUNDEZ-ZANUY. Advanced Parametrization of Graphomotor Difficulties in School-Aged Children. Online. \textit{IEEE Access}. USA: IEEE Xplore Digital Library, 2020, roč.~8, June, s.~112883-112897. ISSN~2169-3536. Dostupné z: https://dx.doi.org/10.1109/ACCESS.2020.3003214. [citováno 2024-04-24]
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