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Analysis of hand-written text of patients with neurological disorders

By Zoltán Galáž


The master‘s thesis deals with the analysis of the hand-written text. There is a design and a realization of a system for the purpose of diagnosing a Parkinson’s desease based on the analysis of hand-written text. The system consists from several modules and it is programmed in the programming environment of MATLAB. The first module provides pre-processing of the records to adjust records to the form suitable for the segmentation. Afterwards, the records are divided into those with signals onto the surface of the tablet and those with the signals above the surface of the tablet. In the next module the records are segmented by the two-phase metod of automatic segmentation.High-level featuresare calculated from the extracted features. The results of the statistical analysis are exported in the form suitable for the classification process. The classification is performed by the proposed model made in the programming environment of RapidMiner. The output of designed system is the trained model capable of automatic classification of the Parkinson’s disease by the analysis of the hand-written text

Topics: segmentation; features; algorithm; strokes; motoric disorders; neural disorders; classification.; neural network; Hand-written text
Publisher: Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Year: 2014
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