Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/77546
Title: Evaluating Parkinson’s Disease in Voice and Handwriting Using the Same Methodology
Authors: Carmona Duarte, María Cristina 
Ferrer Ballester, Miguel Ángel 
Gómez-Vilda, Pedro
Van Gemmert, Arend W. A.
Plamondon, Réjean
UNESCO Clasification: 3307 Tecnología electrónica
Issue Date: 2020
Publisher: World Scientific Publishing 
Abstract: Parkinson’s disease is manifested as well in handwriting as in voice. Different procedures have been used in previous research to estimate the dysfunctions of the illness in voice and handwriting. This paper proposes one parameter to evaluate the influence of the illness on both voice and handwriting as the symptoms affecting these two behaviors have a common origin. Specifically, the parameter proposed is based on the Kinematic Theory of rapid human movements. It allows to quantify the deficits caused by Parkinson’s disease in handwriting and voice. The velocity profile obtained to characterize voice between the first and second formant is computed by a spatio-temporal approximation. In handwriting, the velocity profile is obtained from the sampled positions of the pen on a digitizer tablet. Once the velocity profile is derived, it is transformed to fit into the lognormal model in which similarities between voice and handwriting have been found for the performance of these tasks by Parkinson’s patients. The experiments with different databases of voice and handwriting recorded from different patients in different labs display positive results pointing out a common parameter that is affected by the two types of communication modalities.
URI: http://hdl.handle.net/10553/77546
ISBN: 978-981-12-2682-3
ISSN: 1793-0839
DOI: 10.1142/9789811226830_0007
Source: The Lognormality Principle and its Applications in e-Security, e-Learning and e-Health / Réjean Plamondon; Angelo Marcelli; Miguel Ángel Ferrer (Eds.), p. 161-175
Appears in Collections:Capítulo de libro
Show full item record

Page view(s)

119
checked on May 11, 2024

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.