title: Combining sigma-lognormal modeling and classical features for analyzing graphomotor performances in kindergarten children.
abstract: This paper investigates the advantage of using the kinematic theory of rapid human movements as a complementary approach to those based on classical dynamical features to characterize and analyze kindergarten children's ability to engage in graphomotor activities as a preparation for handwriting learning. This study analyzes nine different movements taken from 48 children evenly distributed among three different school grades corresponding to pupils aged 3, 4, and 5 years. On the one hand, our results show that the ability to perform graphomotor activities depends on kindergarten grades. More importantly, this study shows which performance criteria, from sophisticated neuromotor modeling as well as more classical kinematic parameters, can differentiate children of different school grades. These criteria provide a valuable tool for studying children's graphomotor control learning strategies. On the other hand, from a practical point of view, it is observed that school grades do not clearly reflect pupils' graphomotor performances. This calls for a large-scale investigation, using a more efficient experimental design based on the various observations made throughout this study regarding the choice of the graphic shapes, the number of repetitions and the features to analyze.
authors.affiliation: LAMIA, Université des Antilles et de la Guyane, Campus de Fouillole, Département de mathématiques et informatique, BP 250, 97 159 Pointe à Pitre Cedex, Guadeloupe. Electronic address: tduval@etu.univ-ag.fr.
authors.forename: Thérésa
authors.initials: T
authors.lastname: Duval
authors.affiliation: LAMIA, Université des Antilles et de la Guyane, Campus de Fouillole, Département de mathématiques et informatique, BP 250, 97 159 Pointe à Pitre Cedex, Guadeloupe. Electronic address: cremi@univ-ag.fr.
authors.forename: Céline
authors.initials: C
authors.lastname: Rémi
authors.affiliation: Laboratoire Scribens, Département de Génie Électrique, École Polytechnique de Montréal, C.P. 6079 Succ. Centre-ville, Montréal H3C3A7, Canada. Electronic address: rejean.plamondon@polymtl.ca.
authors.forename: Réjean
authors.initials: R
authors.lastname: Plamondon
authors.affiliation: LAMIA, Université des Antilles et de la Guyane, Campus de Fouillole, Département de mathématiques et informatique, BP 250, 97 159 Pointe à Pitre Cedex, Guadeloupe. Electronic address: jean.vaillant@univ-ag.fr.
authors.forename: Jean
authors.initials: J
authors.lastname: Vaillant
authors.affiliation: Laboratoire Scribens, Département de Génie Électrique, École Polytechnique de Montréal, C.P. 6079 Succ. Centre-ville, Montréal H3C3A7, Canada; Département de psychiatrie, Université de Montréal, 2900 Boulevard Edouard-Montpetit, Montréal, QC H3T 1J4, Canada. Electronic address: christian.oreilly@umontreal.ca.
authors.forename: Christian
authors.initials: C
authors.lastname: O'Reilly
mesh_terms: D000367:Age Factors; D001696:Biomechanical Phenomena; D002648:Child; D002675:Child, Preschool; D005260:Female; D019430:Guadeloupe; D006236:Handwriting; D006801:Humans; D008297:Male; D009048:Motor Skills
keywords: Fine motor control modeling; Handwriting learning; Kindergarten children; Kinematic theory; Movement patterns; Sigma-lognormal