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Data Mining with Python
Krestianková, Tamara ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with principles of data mining process, available Python packages for data mining and a demonstration of Python script capable of data analyisis focused on classification techniques. Created classifiers are able to classify subjects into two groups - healthy people and people suffering from Parkinson's disease - based on their biomedical vocal analysis data.
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State of the art speech features used during the Parkinson disease diagnosis
Bílý, Ondřej ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
This work deals with the diagnosis of Parkinson's disease by analyzing the speech signal. At the beginning of this work there is described speech signal production. The following is a description of the speech signal analysis, its preparation and subsequent feature extraction. Next there is described Parkinson's disease and change of the speech signal by this disability. The following describes the symptoms, which are used for the diagnosis of Parkinson's disease (FCR, VSA, VOT, etc.). Another part of the work deals with the selection and reduction symptoms using the learning algorithms (SVM, ANN, k-NN) and their subsequent evaluation. In the last part of the thesis is described a program to count symptoms. Further is described selection and the end evaluated all the result.
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Virtual reality as a tool for diagnosis and therapy in medicine
Kadlec, Jiří ; Mekyska, Jiří (referee) ; Mucha, Ján (advisor)
The use of virtual reality (VR) in the diagnosis and treatment of severe neurodegenerative or neurodevelopmental diseases is a potential alternative to standard methods and is now the subject of many studies and research. One of the objectives of the thesis is a detailed research and analysis of this usage. Another objective is to research and analyze the options of developing VR applications. The main objective of the thesis is the design and implementation of VR application for therapy and diagnosis of patients with Parkinson's disease. The application contain an adaptive environment and three designed exercises based on existing methods for diagnosis and therapy of patients with PD. Among other things, the application also allow you to store exercise data (such as position and rotation data of controls etc.). The implementation was done in the Unity engine with C# as a programming language, with an emphasis on patient adaptation and minimizing the development of VR disease.
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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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Tool for analysis of subject's movements in functional magnetic resonance measurements.
Šejnoha, Radim ; Lamoš, Martin (referee) ; Gajdoš, Martin (advisor)
This diploma thesis deals with an analysis of subject’s movement during measurements with funcional magnetic resonance imaging (fMRI). It focuses on methods of a movement artifacts detection and their removal in fMRI images. Thesis deals with metrics which are used for the movement rate of measured subjects evaluation. Metrics and a correction of movement are implemented into the programme in MATLAB. Comparison of subjects suffering from Parkinson’s disease with a group of healthy control was carried out. Tresholds of individual metrics were suggested and a criterion for the removal of subjects with high movement rate was determined.
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Nutrition and cerebral neurodegenerative diseases
Šálková, Michaela ; Vespalcová, Milena (referee) ; Vránová, Dana (advisor)
This bachelor‘s thesis is literary research and its topic is focused on the effect of nutrition on the development of neurodegenerative diseases. The thesis is divided into four parts. The first part deals with the structure and physiology of the human brain. In the second part are described all essential nutrients which the brain needs to maintain its functions. The third part focuses on neurodegenerative diseases and their epidemiology and pathophysiology. In this part are also examined nutrients which could be possibly useful in the prevention or which could be involved in the pathophysiology of the disease. Explored diseases include dementia, Alzheimer’s disease, Parkinson’s disease and unipolar depression.The aim of this thesis was to find accessible literature focused on this topic and make a discussion.
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Correlation analysis of Parkinson's disease in the acoustic field
Vošček, Jakub ; Mekyska, Jiří (referee) ; Smékal, Zdeněk (advisor)
The topic of this bachelor thesis is the correlation analysis of Parkinson’s disease in the acoustic field. The first part is about the Parkinson disease and its symptoms. It looks closer on problems with speech production, which is called hypokinetic disarthria, and describes the causes of the problems as well as the kind of treatment that is used. The next part involves a study of the pre–processing of signal, i.e. removing the direct component, a preemphasis and a segmentation to smaller frames. Afterwards, individual parameters are calculated in the next step. It is also necessary to calculate simple statistics, for example a median, a standard deviation, etc. after the calculation of some parameters. The calculation of Pearson’s and Spearman’s correlation coefficients is included. Moreover, a block diagram for the data processing is suggested, which involves a description of the functions of the individual blocks. The program is explained in the practical part, which also features parts of the tables with parameters' values and the calculated coefficients. As the conclusion of the work, there are graphs which display correlations of the parameters and the paraclinical data.
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Identification of sleep disorders based on actigraphy data and sleep diaries
Molík, Miroslav ; Mekyska, Jiří (referee) ; Mikulec, Marek (advisor)
This master’s thesis deals with prediction of Parkinson's disease using sleep parameters from actigraphy and sleep diaries. The goal is to design a machine learning approach, which will be able to recognize pacients suffering from Parkinson's disease. For training dataset supplied by St. Anne's University Hospital Brno was used, which was variously modified for achieving best possible results. These adjustments were evaluated according to the results of the trained models and based on these results, two models (achieving test accuracies of 85 and 82%) were selected.
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Calculation of advanced diffusion parameters in brain grey matter from DKI MRI images
Pánková, Olga ; Jakubíček, Roman (referee) ; Minsterová, Alžběta (advisor)
Thesis named Calculation of advanced diffusion parameters in brain grey matter from DKI MRI images deals with processing of diffusion-weighted images from DKI. The thesis contains review of literature on principle of diffusion, influence of diffusion on MRI, calculation of DTI and DKI parameters and clinical application of diffusion-weighted maps with focus on grey matter. The thesis focuses on software tools for processing and pre-processing DTI and DKI. The practical part consisted of two sections. Two different softwares were used to calculate maps of diffusion parameters. Diffusion parameters from anatomical structure sunstantia nigra were compared between group of healthy controls and patients with Parkinson’s disease. This comparison did not show any statisticaly significant difference. In the second step, a script for creating diffusion maps in software Diffusinal Kurtosis Estimator was made.
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Analysis of Parkinson's disease using segmental speech parameters
Mračko, Peter ; Mekyska, Jiří (referee) ; Smékal, Zdeněk (advisor)
This project describes design of the system for diagnosis Parkinson’s disease based on speech. Parkinson’s disease is a neurodegenerative disorder of the central nervous system. One of the symptoms of this disease is disability of motor aspects of speech, called hypokinetic dysarthria. Design of the system in this work is based on the best known segmental features such as coefficients LPC, PLP, MFCC, LPCC but also less known such as CMS, ACW and MSC. From speech records of patients affected by Parkinson’s disease and also healthy controls are calculated these coefficients, further is performed a selection process and subsequent classification. The best result, which was obtained in this project reached classification accuracy 77,19%, sensitivity 74,69% and specificity 78,95%.
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