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

IEEE International Conference on Bioinformatics and Bioengineering（2015）

Cited 5|Views36

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Abstract

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.

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Key words

automatic analysis,writing tasks,drawing tasks,fine motor skills,Parkinson's disease diagnosis,motor symptoms,PD,feature extraction,movement disorders,essential tremor,ET,functional tremor,FT,enhanced physiological tremor,EPT,classification accuracy

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