2021
DOI: 10.1109/access.2021.3083496
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Design, Implementation and Evaluation of a Support System for Educators and Therapists to Rate the Acquisition of Pre-Writing Skills

Abstract: Assessing the acquisition of pre-writing skills in children with and without special educational needs is a time-consuming task for educators and therapists. It also involves a level of subjectivity, because the same set of strokes may receive different scores from different professionals. We present a system that automates the task by rating the execution of elementary figures (circle, square and triangle) according to the criteria of the Battelle guide for fine motor skills rating. The system uses a neural n… Show more

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Cited by 7 publications
(2 citation statements)
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“…In [42], the authors investigated the influence of pen grasp on handwriting speed and legibility asking children to write on a tablet using a pen instrumented with an array of 64 Tekscan 9811 force sensors applied to the pen barrel [43]. Polsley and colleagues in [44] implemented a machine learning algorithm to automatically recognize drawing patterns important for handwriting (i.e., curvature and corner drawings); Serpa-Andrade et al 2021 in [45] used a neural network trained with a collection of images drawn by 300 children to automatically assess prewriting skills of children based on analytical descriptors (moment invariants [46] or on shape signature [47]). These approaches rely on quantitative features based on the assessment of analytical descriptors.…”
Section: Achievements Limitations and Future Workmentioning
confidence: 99%
“…In [42], the authors investigated the influence of pen grasp on handwriting speed and legibility asking children to write on a tablet using a pen instrumented with an array of 64 Tekscan 9811 force sensors applied to the pen barrel [43]. Polsley and colleagues in [44] implemented a machine learning algorithm to automatically recognize drawing patterns important for handwriting (i.e., curvature and corner drawings); Serpa-Andrade et al 2021 in [45] used a neural network trained with a collection of images drawn by 300 children to automatically assess prewriting skills of children based on analytical descriptors (moment invariants [46] or on shape signature [47]). These approaches rely on quantitative features based on the assessment of analytical descriptors.…”
Section: Achievements Limitations and Future Workmentioning
confidence: 99%
“…Hasil Penelitian sebelumnya yang relevan dengan keterampilan menulis diantaranya (Queroda, 2018) menyatakan bahwa keterampilan pra-menulis perlu dikembangkan pada anak. Senada dengan yang diungkapkan (Serpa-Andrade et al, 2021) bahwa pemerolehan keterampilan pra-menulis juga berkembang pada masa kanak-kanak. Penelitian lain menyebutkan adanya peran perangkat teknologi dalam mengajarkan menulis (Alsamadani, 2017;Yeh et al, 2020).…”
Section: Pendahuluanunclassified