Extraction of dynamic features from hand drawn data for the identification of children with handwriting difficulty

• Main Authors: Khalid, Puspa Inayat, Yunus, Jasmy, Adnan, Robiah
• Format: Article
• Published: Elsevier B.V. 2010
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/26152/; http://dx.doi.org/10.1016/j.ridd.2009.09.009

Studies have shown that differences between children with and without handwriting difficulties lie not only in the written product (static data) but also in dynamic data of handwriting process. Since writing system varies among countries and individuals, this study was conducted to determine the feasibility of using quantitative outcome measures of children's drawing to identify children who are at risk of handwriting difficulties. A sample of 143 first graders of a normal primary school was investigated regarding their handwriting ability. The children were divided into two groups: test and control. Ten children from test group and 40 children from control group were individually tested for their Visual Motor Integration skills. Analysis on dynamic data indicated significant differences between the two groups in temporal and spatial measures of the drawing task performance. Thus, kinematic analysis of children's drawing is feasible to provide performance characteristic of handwriting ability, supporting its use in screening for handwriting difficulty.