| Studying the variability of handwriting patterns using the Kinematic Theory. | |
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MedLine Citation:
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PMID: 19328575 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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The variability observed in handwriting patterns is analyzed from the perspective of integrating the resulting motor control knowledge in the design of more powerful handwriting recognizers in personal digital assistants (PDAs) and smartphones. Using the highest representational level of the Kinematic Theory of Rapid Human Movement, the Sigma-Lognormal model, this article reports basic theoretical and practical results that could be taken into account in the design of such systems. The main movement variability introduced by the neuromuscular system (NMS) and induced through the scheduling of motor tasks by the central nervous system (CNS) is divided into global and local fluctuations. From a fiducial action plan decoded by this model, a wide range of handwriting distortions are artificially generated by acting on the Sigma-Lognormal parameters. The resulting patterns are studied to understand scale changes and rotational deformations, the two basic features that a recognizer has to take into account. An experiment based on the writing of the same word by six writers is also reported. The results, obtained by an ANOVA analysis, corroborate the predictions and support the relevance of the Kinematic Theory for the analysis and synthesis of handwriting disruptions. These findings consolidate the results of previous studies on single strokes using the Sigma-Lognormal model. Overall, this report provides new insights into our understanding of motor control, as well as into practical cues for the development of huge databases of letters and words to train and test on-line handwriting classifiers and recognizers. |
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Authors:
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M Djioua; R Plamondon |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't Date: 2009-03-27 |
Journal Detail:
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Title: Human movement science Volume: 28 ISSN: 1872-7646 ISO Abbreviation: Hum Mov Sci Publication Date: 2009 Oct |
Date Detail:
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Created Date: 2009-09-22 Completed Date: 2010-01-08 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8300127 Medline TA: Hum Mov Sci Country: Netherlands |
Other Details:
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Languages: eng Pagination: 588-601 Citation Subset: IM |
Affiliation:
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D??partement de G??nie Electrique, Laboratoire Scribens, Ecole Polytechnique de Montr??al, Station Centre-Ville, Montr??al QC, Canada H3C 3A7. moussa.djioua@polymtl.ca |
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| MeSH Terms | |
Descriptor/Qualifier:
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Analysis of Variance Biomechanics Brain / physiology Handwriting* Humans Models, Theoretical Motor Activity / physiology Pattern Recognition, Physiological / physiology* Photic Stimulation |
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