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The influence of deep brain stimulation on the brain connectivity
Horváthová, Ľubica ; Výtvarová, Eva (referee) ; Klimeš, Petr (advisor)
Hĺbková mozgová stimulácia (DBS) predstavuje účinnú liečbu pre pacientov s Parkinsonovou chorobou (PD) alebo farmakorezistentnou epilepsiou. Avšak mechanizmy, ktorými znižuje počet záchvatov a zlepšuje pohyb, zostávajú ešte do značnej miery neznáme. Pre lepšie pochopenie a určenie, v ktorých frekvenčných pásmach je zmena najdôležitejšia, boli urobené porovnania medzi vypnutou a zapnutou DBS pomocou korelačnej metódy a indexu fázového posunu. Jedenásť pacientov s PD a naimplantovanými neurostimulátormi z firiem Medtronic a St.Jude Medical bolo predmetom nahraných dát použitých v tejto práci. Výsledky dokazujú, že zmena konektivity počas DBS nastane a zároveň, že najviac ovplyvňuje najvyššie frekvencie ako beta, nízka gama a vysoká gama. Zmeny v týchto frekvenciách, zodpovedné za motorickú aktivitu, sústredenie a spracovanie informácií, sú v súlade s klinickou teóriou o PD. Počas tejto choroby je patologická beta aktivita hypersynchronizovaná a gama aktivita je znížená práve v motorických oblastiach. Ak sa gama aktivita počas zapnutej stimulácie zvyšuje, fyziologický stav pacientov sa čiastočne znovuobnovuje a tým zlepšuje ich hybnosť. Metódy a výsledky tejto práce budú použité pre ďalší výskum pacientov s PD a epilepsiou.
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Library for Python used for dysarthric speech parameterization
Koutný, Tomáš ; Galáž, Zoltán (referee) ; Mucha, Ján (advisor)
Bachelor thesis is focused on parameterization of dysartoric speech. Attention is paid to methods of Speech Signal Analysis for Parkinson's disease, modern parametrization techniques, which are designed to quantify the damage of motoric aspects of speech and implementation of selected parameters in Python. The main goal of this work was to create a parameter library that is realized in the PyCharm development environment.
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Virtual reality as a tool for therapy in medicine
Pecháček, Vilém ; Mekyska, Jiří (referee) ; Mucha, Ján (advisor)
Virtual reality is increasingly the subject of scientific studies dealing with the therapy of neurodegenerative diseases, and its use in combination with conventional therapy appears to be beneficial. The aim of the work is a research of the available literature on this topic and an analysis of commercially available headsets and their technologies. Another of the objectives of the work is the design and implementation of an application for the therapy of motor symptoms of Parkinson's disease with an emphasis on data collection. The application will be developed in the Unreal Engine 5 environment for the Meta Quest 2 headset.
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Use of dance therapy in neurorehabilitation from the perspective of a physiotherapist
Tlustá, Tereza ; Gueye, Tereza (advisor) ; Sládková, Petra (referee)
First and last name: Tereza Tlustá Supervisor: MUDr. Bc.Tereza Gueye Ph.D. Opponent of the thesis: Name of the thesis: Use of dance therapy in neurorehabilitation from the perspective of a physiotherapist. Abstract of the thesis: The bachelor's thesis summarises the present level of knowledge and evidence on the impact of dance therapy on motor symptoms of neurological disorders through a systematic review. The theoretical part provides a comprehensive overview of dance and dance movement therapy and their impact on the musculoskeletal and nervous system. A part of the thesis is also focused on the characteristics and scope of physical rehabilitation of neurological patients and the characteristics of symptoms of some neurological diseases, namely Parkinson's disease and stroke. In the second phase, by analyzing the studies obtained by literature search, fifteen recent and relevant articles were included and analyzed. Through analytical analysis of the results of testing and evaluation of each study, it is determined whether and under what conditions dance therapy was effective. The presented articles include studies testing the effect of dance therapy on stability and gait in Parkinson's disease and post-stroke patients. The paper presents a mostly positive conclusion about the effect of dance...
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Sub-types of hypokinetic dysarthria in patients with moderete Parkinson's disease
Adamják, Adam ; Kováč, Daniel (referee) ; Mekyska, Jiří (advisor)
This final thesis deals with the research of Parkinson's disease, hypokinetic dysarthria, and acoustic and statistical analyses. Hypokinetic dysarthria is a speech disorder that is a typical manifestation of Parkinson's disease, a neurodegenerative disease that affects approximately 2% of the population over the age of 65. The aim of this work is to reveal the subtypes of hypokinetic dysarthria, based on clinical parameters, acoustic analysis, and statistical analysis. In the acoustic analysis, parameters that examine the area of phonation, prosody, articulation, and speech tempo have been implemented. Subsequently, a statistical analysis was processed, thanks to which it was possible to reveal the subtypes of hypokinetic dysarthria.
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Analysis of the spectrum of genetic variants associated with development of Parkinson's disease
Stočesová, Lucie ; Hirschfeldová, Kateřina (advisor) ; Fajkusová, Lenka (referee)
Parkinson's disease (PD) is one of the most common neurodegenerative disease in humans. It affects all age categories and the number of patients with this disease is still growing. However, the genetic cause of PD is not yet very clear and new and new candidate genes are constantly being discovered. The aim of the thesis is to perform a mutation analysis in a group of patients and controls from the Czech population and thus find possible genetic causes of parkinsonism in a cohort of researched patients. The second aim is to evaluate data correlation obtained by different methods. Next generation sequencing was used for this purpose. The results of this sequencing were verified with methods such as MLPA (Multiplex Ligation-Dependent Probe Amplification), analysis of short tandem repeats and Sanger sequencing. Using these methods, we obtained a wide range of possible genetic causes of parkinsonism in the studied group of patients. Patogenic or risk variants were found not only in classical candidate genes typical for PD (called PARK), but also in genes associated with other neurodegenerative diseases. For less than half of the patients (42,64 %), the genetic cause of parkinsonism was not found. Using several methods, we found that next generation sequencing is a very precise method, that can well...
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The role of neuroinflammation in neurodegenerative CNS disease processes
Červenák, Karol ; Novotný, Jiří (advisor) ; Spišská, Veronika (referee)
Inflammatory processes in the CNS are an important element in neuroimmunity. They may be beneficial and have a neuroprotective effect but depending on the extent and duration of their activation they may also have a negative effect on the function of the CNS. Neuroinflammation is characterized by the activation of resident immune cells, microglia and astrocytes, activation of inflammatory signal pathways, recruitment of immune cells from the blood and their penetration through the blood-brain barrier. Chronic neuroinflammation may cause neurodegeneration and is key in the pathogenesis of neurodegenerative diseases. Neurodegeneration is irreversible but it can be mitigated. Therapeutic methods aimed at the modulation of neuroinflammation present a promising option for slowing down or stopping neurodegeneration for people with diseases such as Alzheimer's, Parkinson's, or Huntington's disease. The aim of this thesis is to sum up information about inflammatory processes in the brain and our current knowledge about their role in the pathogenesis of some neurodegenerative diseases. Key words: Inflammation, microglia, neurodegeneration, Alzheimer's disease, Parkinson's disease, Huntington's disease, CNS
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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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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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