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@inproceedings{1602259,
author = {Mekyska, Jiří and Galáž, Zoltan and Šafárová, Katarína and Zvončák, Vojtěch and Mucha, Jan and Smékal, Zdeněk and Ondráčková, Anežka and Urbánek, Tomáš and Havigerová, Jana Marie and Bednářová, Jiřina and FaúndezandZanuy, Marcos},
address = {Dublin, Irsko},
booktitle = {2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)},
doi = {http://dx.doi.org/10.1109/ICUMT48472.2019.8970767},
keywords = {computerised analysis; digitizer; graphomotor difficulties; graphomotor elements; machine learning; online handwriting},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Dublin, Irsko},
isbn = {978-1-72815-763-4},
pages = {1-6},
publisher = {IEEE},
title = {Computerised Assessment of Graphomotor Difficulties in a Cohort of School-aged Children.},
year = {2019}
}
TY - JOUR
ID - 1602259
AU - Mekyska, Jiří - Galáž, Zoltan - Šafárová, Katarína - Zvončák, Vojtěch - Mucha, Jan - Smékal, Zdeněk - Ondráčková, Anežka - Urbánek, Tomáš - Havigerová, Jana Marie - Bednářová, Jiřina - Faúndez-Zanuy, Marcos
PY - 2019
TI - Computerised Assessment of Graphomotor Difficulties in a Cohort of School-aged Children.
PB - IEEE
CY - Dublin, Irsko
SN - 9781728157634
KW - computerised analysis
KW - digitizer
KW - graphomotor difficulties
KW - graphomotor elements
KW - machine learning
KW - online handwriting
N2 - Although graphomotor difficulties (GD) are present in up to 30 % of school-aged children, the field of GD diagnosis and assessment is not fully explored and several research gaps can be identified. This study aims to explore the impact of specific elementary graphomotor tasks analysis on the accuracy of computerised diagnosis and assessment of GD. We analysed seven basic graphomotor tasks from 76 children (assessed by special educational counsellors and using the handwriting proficiency screening questionnaire for children HPSQ–C). Employing a differential analysis, we observed that the most discriminative tasks are based on combined loops, sawtooth and small Archimedean spiral drawings. Features with the highest discrimination power quantify kinematics, especially in the vertical projection. Using a multivariate mathematical model, we were able to identify GD with 50 % sensitivity and 90% specificity, and to estimate the total score of HPSQ–C with 31 % error
ER -
MEKYSKA, Jiří, Zoltan GALÁŽ, Katarína ŠAFÁROVÁ, Vojtěch ZVONČÁK, Jan MUCHA, Zdeněk SMÉKAL, Anežka ONDRÁČKOVÁ, Tomáš URBÁNEK, Jana Marie HAVIGEROVÁ, Jiřina BEDNÁŘOVÁ a Marcos FAÚNDEZ-ZANUY. Computerised Assessment of Graphomotor Difficulties in a Cohort of School-aged Children. Online. In \textit{2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)}. Dublin, Irsko: IEEE, 2019, s.~1-6. ISBN~978-1-72815-763-4. Dostupné z: https://dx.doi.org/10.1109/ICUMT48472.2019.8970767.
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