Advanced Parametrization of Graphomotor Difficulties in School-Aged Children

被引:17
|
作者
Galaz, Zoltan [1 ]
Mucha, Jan [1 ]
Zvoncak, Vojtech [1 ]
Mekyska, Jiri [1 ]
Smekal, Zdenek [1 ]
Safarova, Katarina [2 ]
Ondrackova, Anezka [2 ]
Urbanek, Tomas [2 ]
Havigerova, Jana Marie [2 ]
Bednarova, Jirina [2 ]
Faundez-Zanuy, Marcos [3 ]
机构
[1] Brno Univ Technol, Dept Telecommun, Brno 61600, Czech Republic
[2] Masaryk Univ, Fac Arts, Dept Psychol, Brno 60200, Czech Republic
[3] Escola Super Politecn, Tecnocampus, Mataro 08302, Spain
关键词
Feature extraction; Task analysis; Writing; Statistical analysis; Pediatrics; Psychology; Licenses; Advanced parametrization; computerized analysis; graphomotor difficulties; machine learning; online handwriting; DEVELOPMENTAL DYSGRAPHIA; HANDWRITING PERFORMANCE; ELEMENTARY-SCHOOL; CLASSIFICATION; RELIABILITY; PROFICIENT; PRODUCT; TOOL;
D O I
10.1109/ACCESS.2020.3003214
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:112883 / 112897
页数:15
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