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Diagnosis and progress monitoring of Parkinson’s disease using dysgraphia analysis methods
Markovič, Michal ; Galáž, Zoltán (referee) ; Mekyska, Jiří (advisor)
Parkinson’s disease causes among other symptoms also writing disorder. Parkinson's dysgrafia is disease the writing of parkinsonics. The aim of the work is to show the importance of examinig the parametres of Parkinson's dysgrafia and to find writing parametres, which could distinguish healthy subjects from the pacient and also it could monitoring progress of pakinson's disease. Some of the parametrs showed marked differences and therefore could distinguish healthy people from those with Parkinson’s disease.
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Education-supporting interactive applets
Korbel, Jakub ; Mekyska, Jiří (referee) ; Rajmic, Pavel (advisor)
This bachelor theses is focused to the support of education in branch of image processing. The teoretic part deals with mathematics view to this problematic. The pratical part is focused to creating of web applets (tools for supporting of education) - applets Gamma correction, Rate shape, Bit plane, Numeric minimization convex function.
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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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Acoustic analysis of Mozart effect and its effect in patients with epilepsy
Zemánek, Václav ; Mekyska, Jiří (referee) ; Kiska, Tomáš (advisor)
The music, in generaly, can calm down a human internally. The effect of Mozart’s music can even be measured. Students, who listened Mozart’s music, had higher IQ result and epileptiform activity is describing on patients with epilepsy. This master’s thesis is dealing with design of the evaluation system, which can determine music parameters describing epileptiform activity. In the solution is make detailed analysis of the tracks, signal parameterization, description of data processing and make the Pearson correlation analysis. In the final chapter are described music parameters, which suppress epileptiform activity in the women and the man.
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Semi-automatic computerized system for the segmentation of online handwriting
Gavenčiak, Michal ; Mekyska, Jiří (referee) ; Zvončák, Vojtěch (advisor)
The prevalence of developmental dysgraphia among school children is between 10-30%, yet in Czech Republic, there is no objective method to diagnose it or determine its severity. Past studies have shown the possibility of automatic diagnosis using digital data gathered using a digitizing tablet and a stylus. Data gathered within an ongoing study contain information on position, time stamp, tilt, pressure and azimuth of the stylus. These data are, however, unsuitable for further analysis due unspecified number of exercises contained in one SVC file. Within this thesis the data is analysed and a program, which is able to segment these data into units of exercises and display the processed data on the screen, is designed and implemented.
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Synthesis of the musical audio signal using direct generation of harmonics
Ježek, Štěpán ; Mekyska, Jiří (referee) ; Přikryl, Lubor (advisor)
This thesis is focused on musical sound synthesis, in particular, the method of additive synthesis. The main goal is to implement a software musical instrument in the VST3 plug-in format, using the C++ programming language and the JUCE application framework. The final program offers spectral components editing capabilities and is able to morph between user-defined spectrum states in time. The introduction summarizes some common synthesis methods and their advantages or disadvantages. Next section deals with the technology used during the VST3 plug-in implementation and describes core parts that make up the final application. This analysis is focused mainly on the signal processing part, but there is also a brief description of the graphical user interface.
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Potential calculation of mutual information from a time series
Hubr, Ivo ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
Mutual information is one of the factors used in traffic analysis and preparation phase space. Begin of this work deal with information theory, focusing on the calculation of mutual information. To calculate this parameter has been available for many algorithms which are analyzing in this final work. Two of the algorithms (Fraser-Swinney and calculation of mutual information using adaptive XY subdivision) are applied to the input data Rössler’ attractor, as shown in the output tables and graphs. The third consideration method is the computational Dinh-Tuan-Pham algorithm. The main goal of this work is a comparison of efficiency, speed and accuracy of the calculation of these algorithms.
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Human behaviour monitoring system based on smartphone and bracelet data analysis
Mikulec, Marek ; Zvončák, Vojtěch (referee) ; Mekyska, Jiří (advisor)
There has been established new technological field using smart phones and wearable devices for medical research since the arrival of health 4.0. The main goal of this work is to design, implement and test new system for monitoring people´s behaviour using smart phone and wearable device. These smart compoments should oblige requirements of health~4.0. This work uses open source software AWARE Framework and data from Fitbit API. The final system enables gathering and sharing 36 measurable metrics from smart phone and wearable device. Furthermore it secures efective access to gathered data and puts particular emphasis on the security of the system. Finally the system was used to examine a patterns of REM (Rapid Eye Movement) sleep behaviour disorder.
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Objectification of the Test 3F - dysarthric profile based on acoustic analysis
Bezůšek, Marek ; Galáž, Zoltán (referee) ; Mekyska, Jiří (advisor)
Test 3F is used to diagnose the extent of motor speech disorder – dysarthria for czech speakers. The evaluation of dysarthric speech is distorted by subjective assessment. The motivation behind this thesis is that there are not many automatic and objective analysis tools that can be used to evaluate phonation, articulation, prosody and respiration of speech disorder. The aim of this diploma thesis is to identify, implement and test acoustic features of speech that could be used to objectify and automate the evaluation. These features should be easily interpretable by the clinician. It is assumed that the evaluation could be more precise because of the detailed analysis that acoustic features provide. The performance of these features was tested on database of 151 czech speakers that consists of 51 healthy speakers and 100 patients. Statistical analysis and methods of machine learning were used to identify the correlation between features and subjective assesment. 27 of total 30 speech tasks of Test 3F were identified as suitable for automatic evaluation. Within the scope of this thesis only 10 tasks of Test 3F were tested because only a limited part of the database could be preprocessed. The result of statistical analysis is 14 features that were most useful for the test evaluation. The most significant features are: MET (respiration), relF0SD (intonation), relSEOVR (voice intensity – prosody). The lowest prediction error of the machine learning regression models was 7.14 %. The conclusion is that the evaluation of most of the tasks of Test 3F can be automated. The results of analysis of 10 tasks shows that the most significant factor in dysarthria evaluation is limited expiration, monotone voice and low variabilty of speech intensity.
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