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Event Fixation Related Potential During Visual Emotion Stimulation
Mičánková, Veronika ; Lamoš, Martin (referee) ; Potočňák, Tomáš (advisor)
Cílem této diplomové práce je najít a popsat souvislost mezi fixací očí v emočně zabarveném stimulu, kterým je obrázek či video, a EEG signálu. K tomuto studiu je třeba vyvinout softwarové nástroje v prostředí Matlab k úpravě a zpracování dat získaných z eye trackeru a propojení s EEG signály pomocí nově vytvořených markerů. Na základě získaných znalostí o fixacích, jsou v prostředí BrainVision Analyzeru EEG data zpracovány a následně jsou segmentovány a průměrovány jako evokované potenciály pro jednotlivé stimuly (ERP a EfRP). Tato práce je vypracována ve spolupráci s Gipsa-lab v rámci výzkumného projektu.
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Measurement of biosignals with usage of Biopac system
Rageh, Akram ; Kolářová, Jana (referee) ; Janoušek, Oto (advisor)
This work describes a brief overview of measurement of Electroencephalography (EEG), Electromyography (EMG), Electrooculography (EOG), Electrocardiography (ECG) and theirs usage. Subsequently is described how these biosignals can be measured with Biopac system. The measurement of electrocardiography is described in detail, including ECG curve description, Biopac measurement system and R-R intervals analysis based on measurement of group of volunteers.
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EOG signal processing using Arduino
Typovský, Viktor ; Králík, Martin (referee) ; Harabiš, Vratislav (advisor)
This bachelors thesis deals with scanning and processing EOG signal. Processing means displaying EOG signal detection and eye movement. The theoretical part is first described the formation and properties of EOG signal. Furthermore, they describe factors affecting EOG. The practical part is then given proposal hardware solutions to capture this signal and processing algorithm. Scanning EOG signal is realized by means of the instrumentation amplifier. Its filtration is used lowpass Sallen-Key. It was decided to maintain during scanning DC component of the signal. But that was a problem regarding the electrode potential. This problem would be resolved by the proposed compensation circuit. Processing the resultant signal is then performed in an environment Processing using Arduino platform. EOG imaging algorithm and motion detection functions and is given.
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Sensing eye movement using a device BIOPAC and eyetracker Pupil
Vančurová, Johana ; Mézl, Martin (referee) ; Svozilová, Veronika (advisor)
This bachelor thesis is focused on investigation of visual reaction time of driver using eye movements acquivition. Eye movements were acquired by Biopac device and eyetracker Pupil. The main aim of this work is to compare results of own experiments with points of reference. Theoretical part dealt with anatomy, physiology of eye and describing characteristics of EOG signals. Practical part included experimental measurements to which a group of probands was involved. In the last part of this work the obtained results were compared with the points of reference.
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Positional system of PC interface controled by electrooculogam
Lutz, Jan ; Kolářová, Jana (referee) ; Janoušek, Oto (advisor)
This project treats of the eye physiology and deals with two specific signals of the human eye. These signals are electromyogram and electrooculogram. Reader is briefed by eye’s muscles, ways of measurement EOG signal with Biopac system and possibilities of using this signal as a simple computer interface. Objective of this project is to create a measurement protocol for EOG signal and find out the resolution of the potencial interface. Very important part of this project is filter designed in Matlab, including simple graphics interface. Besides the text, there are several behaviours of the EOG signal, so one can see that the filter is functional. These signals were measured on my own eye and ten signals come from students. On the behaviours is demonstrated solution of my project. Data from each signal are processed in the last chapter.
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Filtering EEG signals
Pohludka, Aleš ; Ronzhina, Marina (referee) ; Potočňák, Tomáš (advisor)
This work describes basics of electroencephalography, measuring methods of electroencephalographic signals, their processing and especially their filtration. The most basic normalised international system for measuring EEG from the scalp is described. The end of theoretical part is dedicated to the most frequent artifacts. The practical part deals with testing two methods based on adaptive filtration of reference EOG signals using the LMS algorithm. Further in the paper are presented tests of before mentioned methods and their verification in practice on gathered signals from volunteers. At the conclusion there is an evaluation of the methods used.
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Fatigue evaluation using electrooculography
Němcová, Andrea ; Vítek, Martin (referee) ; Janoušek, Oto (advisor)
The master´s thesis deals with fatigue evaluation in electrooculography records (EOG). The theoretical part focuses on electrooculography itself, fatigue and methods used for fatigue detection from EOG. The practical part includes a plan of optimal methodology for fatigue evaluation using EOG. The EOG signals are recorded during the volunteers are watching prepared scenes. Those scenes are desribed here. There is also definition of signal processing methods with relevant block diagrams. Laboratory protocol describing EOG signals recording using Biopac data acquisition system is included. Ten volunteers were measured according to this protocol and the signal database was created. In brief questionnaire volunteers were supposed to evaluate fatigue and discomfort of the measurment. Recorded signals were processed and acquired parameters were statistically evaluated. Then the parameters were discussed in terms of fatigue detection ability. On the basis of that software application was created. This application detects fatigue in selected signal. The thesis includes detailed laboratory manual for students.
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Artefacts Removal from Brain EEG Signals Using Adaptive Algorithms
Hatala, Juraj ; Jawed, Soyiba (referee) ; Shakil, Sadia (advisor)
Tato práce se zabývá problémem artefaktů ve záznamech elektroencefalografie (EEG) a metodami jejich odstranění s důrazem na adaptivní filtrace. Artefakty jsou neodmys- litelnou součástí metody EEG a negativně ovlivňují analýzu výsledků tím, že překrývají zájmové mozkové signály. Adaptivní filtrace je všestrannou metodou, kterou lze použít pro odstranění těchto artefaktů, pokud je k dispozici referenční signál korelovaný s arte- faktem. Hlavním cílem této práce je návrh a implementace frameworku, který umožní aplikaci metod adaptivní filtrace na EEG data. Druhotným cílem je posouzení účinnosti nového algoritmu Q-LMS při odstraňování artefaktů z EEG, protože dosud nebyl v tomto scénáři použit. Práce představuje knihovnu v prostředí Python pro adaptivní filtrace EEG a ukazuje a hodnotí experimenty pro scénáře odstraňování artefaktů s použitím Q-LMS fil- tru implementovaného v navržené knihovně. V této knihovně je uživatel schopen vytvářet přizpůsobitelné filtrační pipeliny. Knihovna nabízí různé adaptivní filtry a metody vytváření referenčního signálu s důrazem na zpracování neurologických dat ve formátu BIDS. Uži- vatel však může sdílet vlastní filtry s frameworkem a také používat vlastní vstupní data a referenční signály. Experimenty s Q-LMS algoritmem ukázaly, že se jedná o dobře fun- gující adaptivní algoritmus, avšak výsledky filtrace byly průměrný ve srovnání s výsledky dosaženými jinými standardními adaptivními algoritmy
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