Advanced Analysis of Online Handwriting in a Multilingual Cohort of Patients with Parkinson's Disease

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU131710" target="_blank" >RIV/00216305:26220/19:PU131710 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Advanced Analysis of Online Handwriting in a Multilingual Cohort of Patients with Parkinson's Disease
Original language description
The majority of Parkinson’s disease (PD) patients suffer from handwriting abnormalities commonly called as Parkinsonic dysgraphia. Several approaches of PD dysgraphia analysis exist, e.g. based on online handwriting processing. However, a small and unilingual cohort of PD patients is often an issue in quantitative PD dysgraphia analysis studies. Therefore, in this work, we aim to perform a discrimination analysis in a multilingual cohort of 73 PD patients and 48 healthy controls (Spanish and Czech). For this purpose, we extracted advanced handwriting features based on fractional order derivatives (FD). Discrimination power of the advanced FD-based features was evaluated by Mann-Whitney U test and random forests classifier. We reached 82 % classification accuracy (86 % sensitivity, 77 % specificity) in the multilingual cohort. In addition, we observed high discrimination power of the FD-based parameters and proofed the high impact of online handwriting processing in cross-cultural PD dysgraphia analysis studies.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Advances in Signal Processing and Artificial Intelligence: Proceedings of the 1st International Conference on Advances in Signal Processing and Artificial Intelligence
ISBN
978-84-09-10127-6
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
144-147
Publisher name
International Frequency Sensor Association (IFSA) Publishing, S. L.
Place of publication
Barcelona, Spain
Event location
Barcelona
Event date
Mar 20, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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