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@article{1217615,
author = {Drotár, Peter and Mekyska, Jiří and Rektorová, Irena and Masárová, Lucia and Smékal, Zdeněk and FaundezandZanuy, Marcos},
article_location = {Clare},
article_number = {3},
doi = {http://dx.doi.org/10.1016/j.cmpb.2014.08.007},
keywords = {Handwriting; Disease classification; Parkinson's disease; Micrographia; In-air movement; Decision support systems},
language = {eng},
issn = {0169-2607},
journal = {Computer Methods and Programs in Biomedicine},
title = {Analysis of in-air movement in handwriting: A novel marker for Parkinson's disease},
url = {http://ac.els-cdn.com/S0169260714003204/1-s2.0-S0169260714003204-main.pdf?_tid=002622be-a0ae-11e4-8917-00000aab0f01&acdnat=1421763171_da56b7bd9accd2a6d4b9f54d55183f33},
volume = {117},
year = {2014}
}
TY - JOUR
ID - 1217615
AU - Drotár, Peter - Mekyska, Jiří - Rektorová, Irena - Masárová, Lucia - Smékal, Zdeněk - Faundez-Zanuy, Marcos
PY - 2014
TI - Analysis of in-air movement in handwriting: A novel marker for Parkinson's disease
JF - Computer Methods and Programs in Biomedicine
VL - 117
IS - 3
SP - 405-411
EP - 405-411
PB - Elsevier
SN - 01692607
KW - Handwriting
KW - Disease classification
KW - Parkinson's disease
KW - Micrographia
KW - In-air movement
KW - Decision support systems
UR - http://ac.els-cdn.com/S0169260714003204/1-s2.0-S0169260714003204-main.pdf?_tid=002622be-a0ae-11e4-8917-00000aab0f01&acdnat=1421763171_da56b7bd9accd2a6d4b9f54d55183f33
N2 - Background and objective: Parkinson's disease (PD) is the second most common neurodegenerative disease affecting significant portion of elderly population. One of the most frequent hallmarks and usually also the first manifestation of PD is deterioration of handwriting characterized by micrographia and changes in kinematics of handwriting. There is no objective quantitative method of clinical diagnosis of PD. It is thought that PD can only be definitively diagnosed at postmortem, which further highlights the complexities of diagnosis. Methods: We exploit the fact that movement during handwriting of a text consists not only from the on-surface movements of the hand, but also from the in-air trajectories performed when the hand moves in the air from one stroke to the next. We used a digitizing tablet to assess both in-air and on-surface kinematic variables during handwriting of a sentence in 37 PD patients on medication and 38 age- and gender-matched healthy controls. Results: By applying feature selection algorithms and support vector machine learning methods to separate PD patients from healthy controls, we demonstrated that assessing the in-air/on-surface hand movements led to accurate classifications in 84% and 78% of subjects, respectively. Combining both modalities improved the accuracy by another 1% over the evaluation of in-air features alone and provided medically relevant diagnosis with 85.61% prediction accuracy. Conclusions: Assessment of in-air movements during handwriting has a major impact on disease classification accuracy. This study confirms that handwriting can be used as a marker for PD and can be with advance used in decision support systems for differential diagnosis of PD.
ER -
DROTÁR, Peter, Jiří MEKYSKA, Irena REKTOROVÁ, Lucia MASÁROVÁ, Zdeněk SMÉKAL and Marcos FAUNDEZ-ZANUY. Analysis of in-air movement in handwriting: A novel marker for Parkinson's disease. \textit{Computer Methods and Programs in Biomedicine}. Clare: Elsevier, vol.~117, No~3, p.~405-411. ISSN~0169-2607. doi:10.1016/j.cmpb.2014.08.007. 2014.
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