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DROTÁR, P. MEKYSKA, J. REKTOROVÁ, I. MASÁROVÁ, L. SMÉKAL, Z. FAÚNDEZ ZANUY, M.
Original Title
Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson's disease
Type
journal article in Web of Science
Language
English
Original Abstract
We present the PaHaW Parkinson's disease handwriting database, consisting of handwriting samples from Parkinson's disease (PD) patients and healthy controls. Our goal is to show that kinematic features and pressure features in handwriting can be used for the differential diagnosis of PD. The database contains records from 37 PD patients and 38 healthy controls performing eight different handwriting tasks. The tasks include drawing an Archimedean spiral, repetitively writing orthographically simple syllables and words, and writing of a sentence. In addition to the conventional kinematic features related to the dynamics of handwriting, we investigated new pressure features based on the pressure exerted on the writing surface. To discriminate between PD patients and healthy subjects, three different classifiers were compared: K-nearest neighbors (K-NN), ensemble AdaBoost classifier, and support vector machines (SVM). For predicting PD based on kinematic and pressure features of handwriting, the best performing model was SVM with classification accuracy of Pacc = 81.3% (sensitivity Psen = 87.4% and specificity of Pspe = 80.9%). When evaluated separately, pressure features proved to be relevant for PD diagnosis, yielding Pacc = 82.5% compared to Pacc = 75.4% using kinematic features. Experimental results showed that an analysis of kinematic and pressure features during handwriting can help assess subtle characteristics of handwriting and discriminate between PD patients and healthy controls.
Keywords
Decision support system, support vector machine classifier, handwriting database, handwriting pressure, Parkinson's disease, PD dysgraphia
Authors
DROTÁR, P.; MEKYSKA, J.; REKTOROVÁ, I.; MASÁROVÁ, L.; SMÉKAL, Z.; FAÚNDEZ ZANUY, M.
Released
1. 2. 2016
ISBN
0933-3657
Periodical
ARTIFICIAL INTELLIGENCE IN MEDICINE
Year of study
67
Number
1
State
Kingdom of the Netherlands
Pages from
39
Pages to
46
Pages count
8
BibTex
@article{BUT123874, author="Peter {Drotár} and Jiří {Mekyska} and Irena {Rektorová} and Lucia {Masárová} and Zdeněk {Smékal} and Marcos {Faúndez Zanuy}", title="Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson's disease", journal="ARTIFICIAL INTELLIGENCE IN MEDICINE", year="2016", volume="67", number="1", pages="39--46", doi="10.1016/j.artmed.2016.01.004", issn="0933-3657" }