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Advanced parametrization of graphomotor difficulties in school-aged children

Resource identifiers

Galaz Z, Mucha J, Zvončák V, Mekyska J, Smekal Z, Zvončáková K, Ondráčková A, Urbanek T, Havigerova JM, Bednarova J, Faundez-Zanuy M. Advanced parametrization of graphomotor difficulties in school-aged children. IEEE Acces. 2020 Jun 17;8:112883-112897. DOI: 10.1109/ACCESS.2020.3003214

2169-3536

http://hdl.handle.net/20.500.12367/2511

10.1109/ACCESS.2020.3003214

Origin

(Repositori Digital del TecnoCampus)

File

Title:: Advanced parametrization of graphomotor difficulties in school-aged children
Subject:: Advanced parametrization; Computerized analysis; Graphomotor difficulties; Machine learning; Online handwriting
Description:: 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. [...]; info:eu-repo/semantics/publishedVersion
Idioma:: English
Relationship:: IEEE Acces. 2020 Jun 17;8:112883-112897
Author/Producer:: Galaz, Zoltan; Mucha, Ján; Zvončák, Vojtěch; Mekyska, Jiri; Smekal, Zdenek; Zvončáková, Katarína; Ondráčková, Anežka; Urbanek, Tomas; Havigerova, Jana Marie; Bednarova, Jirina; Faundez-Zanuy, Marcos
Editor:: IEEE
Rights:: Attribution 4.0 International; http://creativecommons.org/licenses/by/4.0/; info:eu-repo/semantics/openAccess
Date:: 2023-11-23T11:37:50Z; 2020-06-17
Resource type:: info:eu-repo/semantics/article
Format:: 15 p.; application/pdf

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1. < dc:title > Advanced parametrization of graphomotor difficulties in school-aged children </ dc:title >
2. < dc:creator > Galaz, Zoltan </ dc:creator >
3. < dc:creator > Mucha, Ján </ dc:creator >
4. < dc:creator > Zvončák, Vojtěch </ dc:creator >
5. < dc:creator > Mekyska, Jiri </ dc:creator >
6. < dc:creator > Smekal, Zdenek </ dc:creator >
7. < dc:creator > Zvončáková, Katarína </ dc:creator >
8. < dc:creator > Ondráčková, Anežka </ dc:creator >
9. < dc:creator > Urbanek, Tomas </ dc:creator >
10. < dc:creator > Havigerova, Jana Marie </ dc:creator >
11. < dc:creator > Bednarova, Jirina </ dc:creator >
12. < dc:creator > Faundez-Zanuy, Marcos </ dc:creator >
13. < dc:subject > Advanced parametrization </ dc:subject >
14. < dc:subject > Computerized analysis </ dc:subject >
15. < dc:subject > Graphomotor difficulties </ dc:subject >
16. < dc:subject > Machine learning </ dc:subject >
17. < dc:subject > Online handwriting </ dc:subject >
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        < field name =" value " > 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. [...] </ field >
        
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