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Degree of Parkinson's disease estimation based on acoustic analysis of speech
Ustohalová, Iveta ; Kiska, Tomáš (referee) ; Galáž, Zoltán (advisor)
The diploma thesis deals with the non-invasive analysis of progression of Parkinson´s disease using the acoustic analysis of speach. Hypokinetic dysarthria in connection with Parkinson´s disease as well as speech parameters are described in this work. Speech parameters are sorted according to the speech component they affect. The work uses the phonation of vowels "a" speech task as the most commonly used speech task in the field of pathological speech processing, because of its resistance to demographic and linguistic characteristics of the speakers. Based on obtained knowledge, in MATLAB development enviroment were created systém for UPDRS III scale estimation. The UPDRS III scale is based on subjective diagnosis given by the doctor. At first, one individual parameter is used for the UPDRS III scale value estimation. Then the feature selection using SFFS algorithm is applied to gain feature combination with minimal estimation errror. Attention i salso paid to correlation between individual symptoms and UPDSR III scale.
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Analysis of hand-written text of patients with neurological disorders
Galáž, Zoltán ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
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.
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Degree of Parkinson's disease estimation based on acoustic analysis of speech
Ustohalová, Iveta ; Kiska, Tomáš (referee) ; Galáž, Zoltán (advisor)
The diploma thesis deals with the non-invasive analysis of progression of Parkinson´s disease using the acoustic analysis of speach. Hypokinetic dysarthria in connection with Parkinson´s disease as well as speech parameters are described in this work. Speech parameters are sorted according to the speech component they affect. The work uses the phonation of vowels "a" speech task as the most commonly used speech task in the field of pathological speech processing, because of its resistance to demographic and linguistic characteristics of the speakers. Based on obtained knowledge, in MATLAB development enviroment were created systém for UPDRS III scale estimation. The UPDRS III scale is based on subjective diagnosis given by the doctor. At first, one individual parameter is used for the UPDRS III scale value estimation. Then the feature selection using SFFS algorithm is applied to gain feature combination with minimal estimation errror. Attention i salso paid to correlation between individual symptoms and UPDSR III scale.
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Analysis of hand-written text of patients with neurological disorders
Galáž, Zoltán ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
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.
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Analysis of hand-written text of patients with neurological disorders
Galáž, Zoltán ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
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.
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