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Development, maturation and learning influence on handwriting kinematics
- Source :
- Human Movement Science. 32:136-146
- Publication Year :
- 2013
- Publisher :
- Elsevier BV, 2013.
-
Abstract
- Handwriting is the result of a process in which linguistic, psychomotor and biomechanical factors interact with physical maturation, cognitive development and learning. Digital tablets, which record the writing in real time, allow a kinematic analysis of written trace: the implemented algorithms analyze parameters as length, duration and speed of the components (trace between two pen-lifts) and strokes (trace between two minima of curvilinear velocity). The purpose of this work is to fill, at least for Italy, the lack of normative data on typical handwriting processes. This cross-sectional study will present data on 218 right-handed and Italian mother-tongue students, attending classes from 2nd to 8th grade. They performed specific tasks (tests of writing speed; transcription of a sentence accurately vs. speedily) by a digital tablet. The analysis showed many changes of the considered parameters across the classes, as in the horizontal, curvilinear mean and peak velocities of components and strokes, with higher values in the last years of schooling and a parallel decrease in the number of strokes/letter (improvement of automation). In conclusion, some of these parameters are useful for studying development and learning of writing and their values can be used as references to evaluate samples with different characteristics.
- Subjects :
- Male
Handwriting
Adolescent
Computer science
Speech recognition
Biophysics
Experimental and Cognitive Psychology
Kinematics
computer.software_genre
Language Development
Child Development
Cognition
Transcription (linguistics)
Reference Values
Orientation
Reaction Time
Cognitive development
Humans
Orthopedics and Sports Medicine
Handwriting kinematics
Child
Language
Psychomotor learning
maturation
motor learning
business.industry
Automatism
General Medicine
Handwriting kinematic
Biomechanical Phenomena
Trace (semiology)
Space Perception
Female
Artificial intelligence
business
Motor learning
computer
Psychomotor Performance
Natural language processing
Sentence
Subjects
Details
- ISSN :
- 01679457
- Volume :
- 32
- Database :
- OpenAIRE
- Journal :
- Human Movement Science
- Accession number :
- edsair.doi.dedup.....1d238da35943ce93ef3033c25c5474f4