National Repository of Grey Literature 59 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Structural and functional connectivity assessment in patients with Parkinson's disease
Klobušiaková, Patrícia ; Keller, Jiří (referee) ; Mekyska, Jiří (advisor)
Early changes in visuospatial functions predict dementia in Parkinson’s disease (PD). The aim of this work is to assess both structural and functional connectivity of the fasciculus longitudinalis inferior (ILF), which is engaged in visuospatial processing, in PD patients in comparison to healthy controls, and to find associations between connectivity changes and cognitive performance in the patient groups with or without mild cognitive impairment (MCI). To achieve our goal we recruited PD patients with normal cognition (PD-NC, n = 23) and PD with MCI (PD-MCI, n = 21) as well as healthy controls (HC, n = 48). Bidirectional iterative parcellation was used to isolate ILF tracts and their respective endpoints (occipital lobe and anterior temporal lobe) in each subject. The endpoints then served as regions of interest for functional connectivity calculation. We found ILF microstructural connectivity impairment in PD-MCI group, as measured by mean diffusivity, fractional anisotropy and radial diffusivity. In addition, the functional connectivity of ILF tracts was decreased already in the PD-NC. Both structural and functional connectivity deterioration was associated with visuospatial dysfunction in PD-MCI. These changes could serve as potential markers of disease progression or treatment effects monitoring.
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.
Differential analysis of multilingual corpus in patients with neurodegenerative diseases
Kováč, Daniel ; Zvončák, Vojtěch (referee) ; Mekyska, Jiří (advisor)
This diploma thesis focuses on the automated diagnosis of hypokinetic dysarthria in the multilingual speech corpus, which is a motor speech disorder that occurs in patients with neurodegenerative diseases such as Parkinson’s disease. The automatic speech recognition approach to diagnosis is based on the acoustic analysis of speech and subsequent use of mathematical models. The popularity of this method is on the rise due to its objectivity and the possibility of working simultaneously on different languages. The aim of this work is to find out which acoustic parameters have high discriminative power and are universal for multiple languages. To achieve this, a statistical analysis of parameterized speech tasks and subsequent modelling by machine learning methods was used. The analyses were performed for Czech, American English, Hungarian and all languages together. It was found that only some parameters enable the diagnosis of the hypokinetic disorder and are, at the same time, universal for multiple languages. The relF2SD parameter shows the best results, followed by the NST parameter. When classifying speakers of all the languages together, the model achieves accuracy of 59 % and sensitivity of 72 %.
System of secured actigraph data transfer and processing
Mikulec, Marek ; Galáž, Zoltán (referee) ; Mekyska, Jiří (advisor)
The new Health 4.0 concept brings the idea of combining modern technologies from field of science and technology with research in healthcare and medicine. This work realizes a system of secured actigraph data transfer and preprocessing based on the concept of Health 4.0. The system is successfully designed, implemented, tested and secured. With the help of a non-invasive method of monitoring the movement and temperature of the subject using the GENEActiv actigraph allows the system to securely transfer, process and evaluate the subject's sleep data using the machine learning algorithm XGBoost. The proposed system is in accordance with the valid law of the Czech Republic and meets legal requirements.
Audio Classification with Deep Learning on Limited Data Sets
Harár, Pavol ; Platoš,, Jan (referee) ; Šimák, Boris (referee) ; Mekyska, Jiří (advisor)
Standardní postupy diagnózy dysfonie klinickým logopedem mají své nevýhody, především tu, že je tento proces velmi subjektivní. Nicméně v poslední době získala popularitu automatická objektivní analýza stavu mluvčího. Vědci úspěšně založili své metody na různých algoritmech strojového učení a ručně vytvořených příznacích. Tyto metody nejsou bohužel přímo škálovatelné na jiné poruchy hlasu, samotný proces tvorby příznaků je pracný a také náročný z hlediska financí a talentu. Na základě předchozích úspěchů může přístup založený na hlubokém učení pomoci překlenout některé problémy se škálovatelností a generalizací, nicméně překážkou je omezené množství trénovacích dat. Jedná se o společný jmenovatel téměř ve všech systémech pro automatizovanou analýzu medicínských dat. Hlavním cílem této práce je výzkum nových přístupů prediktivního modelování založeného na hlubokém učení využívající omezené sady zvukových dat, se zaměřením zejména na hodnocení patologických hlasů. Tato práce je první, která experimentuje s hlubokým učením v této oblasti, a to na dosud největší kombinované databázi dysfonických hlasů, která byla v rámci této práce vytvořena. Předkládá důkladný průzkum veřejně dostupných zdrojů dat a identifikuje jejich limitace. Popisuje návrh nových časově-frekvenčních reprezentací založených na Gaborově transformaci a představuje novou třídu chybových funkcí, které přinášejí reprezentace výstupů prospěšné pro učení. V numerických experimentech demonstruje zlepšení výkonu konvolučních neuronových sítí trénovaných na omezených zvukových datových sadách pomocí tzv. "augmented target loss function" a navržených časově-frekvenčních reprezentací "Gabor" a "Mel scattering".
Music information retrieval techniques for determining the place of origin of the Czech chamber and orchestral music interpretations
Miklánek, Štěpán ; Mekyska, Jiří (referee) ; Kiska, Tomáš (advisor)
This diploma thesis is focused on the statistical analysis of chamber and orchestral classical music recordings composed by Czech authors. One of the chapters is dedicated to the description of a feature extraction process that precedes the statistical analysis. Techniques of Music Information Retrieval are used during several stages of this thesis. Databases used for analysis are described and pre-processing steps are proposed. A tool for synchronization of the recordings was implemented in MATLAB. Finally the system used for classification of recordings based on their geographical origin is proposed. The recordings are sorted by a binary classifier into two categories of Czech and world recordings. The first part of the statistical analysis is focused on individual analysis of features. The features are evaluated based on their discrimination strength. The second part of the statistical analysis is focused on feature selection, which can improve the overall accuracy of the binary classifier compared to the individual analysis of the features.
Patient assessment system based on mHealth techniques
Kulinich, Viacheslav ; Mucha, Ján (referee) ; Mekyska, Jiří (advisor)
This bachelor thesis is focused on the possibility of examining patients using an electronic questionnaire based on mHealth techniques. In the first two chapters of this work is included the issue of patient examination, the function that must fulfill the electronic questionnaire, the research of existing types of mobile applications and the description of the selected type. The following chapters contain the process of creating web applications, implementation of client and server part, their communication, used security elements and brief description of graphical interface. The result is a functional progressive web application that has been tested successfully and is published on the Internet.
Android application for clinical assessment of patients
Rusnák, Daniel ; Galáž, Zoltán (referee) ; Mekyska, Jiří (advisor)
This bachelor thesis deals with the design and implementation of a system for digitizing the process of clinical testing of patients with neurological diseases in the form of test questionnaires. The system consists of three applications that together form a functional system to help doctors work efficiently and speed up their work.
Face parameterization using videosequence
Lieskovský, Pavol ; Mekyska, Jiří (referee) ; Rajnoha, Martin (advisor)
This work deals with the problem of face parameterization from the video of a speaking person and estimating Parkinson’s disease and the progress of its symptoms based on face parameters. It describes the syntax and function of the program that was created within this work and solves the problem of face parameterization. The program formats the processed data into a time series of parameters in JSON format. From these data, a dataset was created, based on which artificial intelligence models were trained to predict Parkinson’s disease and the progress of its symptoms. The process of model training and their results are documented within this work.
Analysis of Expressive Music Performance using Digital Signal Processing Methods
Ištvánek, Matěj ; Mekyska, Jiří (referee) ; Smékal, Zdeněk (advisor)
This diploma thesis deals with methods of the onset and tempo detection in audio signals using specific techniques of digital processing. It analyzes and describes the issue from both the musical and the technical side. First, several implementations using different programming environments are tested. The system with the highest detection accuracy and adjustable parameters is selected, which is then used to test functionality on the reference database. Then, an extension of the algorithm based on the Teager-Kaiser energy operator in the preprocessing stage is created. The difference in accuracy of both systems is compared – the operator has on average increased the accuracy of detection of a global tempo and inter-beat intervals. Finally, a second dataset containing 33 different interpretations of the first movement of Bedřich Smetana’s composition, String Quartet No. 1 in E minor "From My Life". The results show that the average tempo of the entire first movement of the song slightly decreases depending on the later year of the recording.

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