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Advanced Parkinson's Disease Dysgraphia Analysis Based on Fractional Derivatives of Online Handwriting

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14740%2F18%3A00108296" target="_blank" >RIV/00216224:14740/18:00108296 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/ICUMT.2018.8631265" target="_blank" >http://dx.doi.org/10.1109/ICUMT.2018.8631265</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ICUMT.2018.8631265" target="_blank" >10.1109/ICUMT.2018.8631265</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Advanced Parkinson's Disease Dysgraphia Analysis Based on Fractional Derivatives of Online Handwriting

  • Original language description

    Parkinson's disease (PD) is one of the most frequent neurodegenerative disorder with progressive decline in several motor and non-motor skills. Due to time-consuming and partially subjective conventional PD diagnosis, several more effective approaches based on signal processing and machine learning, e.g. online handwriting analysis, have been proposed. This paper introduces a new methodology of PD dysgraphia analysis based on fractional derivatives applied in PD handwriting quantification. The proposed methodology was evaluated on a database that consists 33 PD patients and 36 healthy controls who performed several handwriting tasks. Employing random forests classifier in combination with 5 kinematic features based on fractionalorder derivatives we reached 90% classification accuracy, 89% sensitivity, and 91% specificity. In comparison with the results of other related works dealing with the same database, the proposed approach brings improvements in PD dysgraphia diagnosis and confirms the impact of fractional derivatives in kinematic analysis.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    30103 - Neurosciences (including psychophysiology)

Result continuities

  • 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)

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2018 10TH INTERNATIONAL CONGRESS ON ULTRA MODERN TELECOMMUNICATIONS AND CONTROL SYSTEMS AND WORKSHOPS (ICUMT 2018): EMERGING TECHNOLOGIES FOR CONNECTED SOCIETY

  • ISBN

    9781538693605

  • ISSN

    2157-0221

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    „IEEE,IEEEReg8“-„5“

  • Publisher name

    IEEE

  • Place of publication

    NEW YORK

  • Event location

    Moscow, RUSSIA

  • Event date

    Nov 5, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000459238500067