2026-04-13T05:47:48Zhttps://recercat.cat/oai/request
oai:recercat.cat:20.500.12367/25112026-02-18T08:59:26Zcom_2072_484362col_2072_484363
RECERCAT author Galaz, Zoltan author Mucha, Ján author Zvončák, Vojtěch author Mekyska, Jiri author Smekal, Zdenek author Zvončáková, Katarína author Ondráčková, Anežka author Urbanek, Tomas author Havigerova, Jana Marie author Bednarova, Jirina author Faundez-Zanuy, Marcos 2026-02-18T08:59:26Z 2026-02-18T08:59:26Z 2020-06-17 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 https://hdl.handle.net/20.500.12367/2511 10.1109/ACCESS.2020.3003214 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. [...] eng Attribution 4.0 International Advanced parametrization Computerized analysis Graphomotor difficulties Machine learning Online handwriting Advanced parametrization of graphomotor difficulties in school-aged children info:eu-repo/semantics/article