Effect of Stroke-level Intra-writer Normalization on Computerized Assessment of Developmental Dysgraphia
| Authors | |
|---|---|
| Year of publication | 2018 |
| Type | Article in Proceedings |
| Conference | 10th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT) |
| MU Faculty or unit | |
| Citation | |
| Web | https://ieeexplore.ieee.org/document/8631271 |
| Doi | http://dx.doi.org/10.1109/ICUMT.2018.8631271 |
| Keywords | developmental dysgraphia; digitizer; intrawriter normalization; kinematic analysis; machine learning; online handwriting |
| Description | Developmental dysgraphia (DD) can negatively influence writing speed, legibility of written product, and even planning and content generation. This could have a detrimental impact on self-expression, and communication in childhood. The goal of this study is to investigate new intra-writer and selfesteem normalization methods (IWN) in direction of improving computerized DD assessment based on the quantitative analysis of online handwriting. For this purpose we enrolled 97 children who wrote a paragraph using a digitizing tablet. Their handwriting proficiency was rated by the Handwriting Proficiency Screening Questionnaire (HPSQ). The handwriting was parametrized using a conventional set of features that were consequently normalized by four newly designed IWN. Based on the results we observed that a stroke-level ‘ 2 norm normalization decreased the computerized DD assessment error from 23% to 18%. This study proves that the stroke-level IWN has the significant potential in the field of computerized DD diagnosis and assessment. |
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