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Open Access Open Badges Methodology

Automatic assessment of the motor state of the Parkinson's disease patient--a case study

Bozena Kostek1*, Katarzyna Kaszuba1, Pawel Zwan1, Piotr Robowski23 and Jaroslaw Slawek23

Author Affiliations

1 Multimedia Systems Department, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk, Poland

2 Department of Neurology and Movement Disorders, St Adalbert Hospital, Gdańsk, Poland

3 Department of Neurological-Psychiatric Nursing, Medical University of Gdansk, Gdansk, Poland

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Diagnostic Pathology 2012, 7:18  doi:10.1186/1746-1596-7-18

Published: 19 February 2012


This paper presents a novel methodology in which the Unified Parkinson's Disease Rating Scale (UPDRS) data processed with a rule-based decision algorithm is used to predict the state of the Parkinson's Disease patients. The research was carried out to investigate whether the advancement of the Parkinson's Disease can be automatically assessed. For this purpose, past and current UPDRS data from 47 subjects were examined. The results show that, among other classifiers, the rough set-based decision algorithm turned out to be most suitable for such automatic assessment.

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Parkinson's disease; UPDRS; Rule-based decision algorithms; Rough sets