Original title: New Methodology Of Parkinsonic Dysgraphia Analysis By Online Handwriting Using Fractional Derivatives
Authors: Mucha, Ján
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: Parkinson’s disease (PD) is the second most frequent neurodegenerative disorder. One typical hallmark of PD is disruption in execution of practised skills such as handwriting. This paper introduces a new methodology of kinematic features calculation based on fractional derivatives applied on PD handwriting. Discrimination power of basic kinematic features (velocity, acceleration, jerk) was evaluated by classification analysis (using support vector machines and random forests). For this purpose, 37 PD patients and 38 healthy controls were enrolled. In comparison to results reported in other works, we proved that FDE in online handwriting analysis brings promising improvements. The best result of multivariate analysis was achieved with 83:89% classification accuracy in combination with 5 features using only one handwriting task (overlapped circles). This study reveals an impact of fractional derivatives based features in analysis of Parkinsonic dysgraphia.
Keywords: Binary classification; fractal calculus; fractional derivative; online handwriting; overlapped circles; Parkinson’s disease
Host item entry: Proceedings of the 24th Conference STUDENT EEICT 2018, ISBN 978-80-214-5614-3

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/138264

Permalink: http://www.nusl.cz/ntk/nusl-393450


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