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Publication detail
MUCHA, J.
Original Title
NEW METHODOLOGY OF PARKINSONIC DYSGRAPHIA ANALYSIS BY ONLINE HANDWRITING USING FRACTIONAL DERIVATIVES
Type
conference paper
Language
English
Original 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
Authors
Released
26. 4. 2018
Location
BRNO
ISBN
978-80-214-5614-3
Book
Proceedings of the 24nd Conference STUDENT EEICT 2018
Pages from
398
Pages to
402
Pages count
5
URL
http://www.feec.vutbr.cz/EEICT/archiv/sborniky/EEICT_2018_sbornik.pdf
BibTex
@inproceedings{BUT147110, author="Ján {Mucha}", title="NEW METHODOLOGY OF PARKINSONIC DYSGRAPHIA ANALYSIS BY ONLINE HANDWRITING USING FRACTIONAL DERIVATIVES", booktitle="Proceedings of the 24nd Conference STUDENT EEICT 2018", year="2018", pages="398--402", address="BRNO", isbn="978-80-214-5614-3", url="http://www.feec.vutbr.cz/EEICT/archiv/sborniky/EEICT_2018_sbornik.pdf" }