Distinguishing Parkinson's disease from other syndromes causing tremor using automatic analysis of writing and drawing tasks

Antti Tolonen, Luc Cluitmans, Esther Smits, Mark van Gils, Natasha Maurits, Rutger Zietsma

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    4 Citations (Scopus)


    An easily performed and objective test of patients fine motor skills would be valuable in the diagnosis of Parkinson's disease (PD). In this study we present a set of automatic methods for quantifying the motor symptoms of PD and show that these automatically extracted features can be used to distinguish PD from other movement disorders causing tremor, namely essential tremor (ET), functional tremor (FT) and enhanced physiological tremor (EPT). The classification accuracies (mean of sensitivity and specificity) for separating PD from the other tremor syndromes were 82.0 % for ET, 69.8 % for FT and 72.2 % for EPT.
    Original languageEnglish
    Title of host publicationBioinformatics and Bioengineering (BIBE), 2015 IEEE 15th International Conference on
    PublisherIEEE Institute of Electrical and Electronic Engineers
    ISBN (Electronic)978-1-4673-7983-0, 978-1-4673-7982-3
    ISBN (Print)978-1-4673-7984-7
    Publication statusPublished - 2015
    MoE publication typeA4 Article in a conference publication
    Event15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015 - Belgrade, Serbia
    Duration: 2 Nov 20154 Nov 2015
    Conference number: 15


    Conference15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015
    Abbreviated titleBIBE 2015

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