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Variability of Grip Kinetics during Adult Signature Writing

Grip kinetics and their variation are emerging as important considerations in the clinical assessment of handwriting pathologies, fine motor rehabilitation, biometrics, forensics and ergonomic pen design. This study evaluated the intra- and inter-participant variability of grip shape kinetics in adu...

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Detalles Bibliográficos
Autores principales: Ghali, Bassma, Thalanki Anantha, Nayanashri, Chan, Jennifer, Chau, Tom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3642185/
https://www.ncbi.nlm.nih.gov/pubmed/23658812
http://dx.doi.org/10.1371/journal.pone.0063216
Descripción
Sumario:Grip kinetics and their variation are emerging as important considerations in the clinical assessment of handwriting pathologies, fine motor rehabilitation, biometrics, forensics and ergonomic pen design. This study evaluated the intra- and inter-participant variability of grip shape kinetics in adults during signature writing. Twenty (20) adult participants wrote on a digitizing tablet using an instrumented pen that measured the forces exerted on its barrel. Signature samples were collected over 10 days, 3 times a day, to capture temporal variations in grip shape kinetics. A kinetic topography (i.e., grip shape image) was derived per signature by time-averaging the measured force at each of 32 locations around the pen barrel. The normalized cross correlations (NCC) of grip shape images were calculated within- and between-participants. Several classification algorithms were implemented to gauge the error rate of participant discrimination based on grip shape kinetics. Four different grip shapes emerged and several participants made grip adjustments (change in grip shape or grip height) or rotated the pen during writing. Nonetheless, intra-participant variation in grip kinetics was generally much smaller than inter-participant force variations. Using the entire grip shape images as a 32-dimensional input feature vector, a K-nearest neighbor classifier achieved an error rate of [Image: see text]% in discriminating among participants. These results indicate that writers had unique grip shape kinetics that were repeatable over time but distinct from those of other participants. The topographic analysis of grip kinetics may inform the development of personalized interventions or customizable grips in clinical and industrial applications, respectively.