Title: Correlation between mental stress, trapezius muscles electrical activity and electrical activity of the brain Objectives: The main goal of this thesis is to find out whether a shortterm mental stress induced by solving tests in maths, Czech language and colour word test in a time pressure increases the electrical activity in musculus trapezius and further more to evaluate the change in distribution of alfa activity in electroencephalographic record before and after undertaking the above mentioned tests. Methods: The experimental sample consisted of six university students (5 women, 1 man) at the age from 22 to 30. The electrical activity of m. trapezius pars descendens was being evaluated billateraly using the telemetric surface electromyography TeleMyo Mini of the Neurodata company, and electrical activity of the brain was being evaluated using the EEG Nicolet. The stress load was induced by solving mental tests (Czech language, mathematics and a colour word test) in a time limit. The shorten version of Eysenck Personality Questionnaire was used to determine the characteristics of the individuals. We focused mainly on determining degree of neuroticism. Results: No influence of mental load on increasing the electric activity of m. trapezius pars descendens was proven. Electroencephalographic...

The first aim was to determine the baseline psychophysiological correlates in healthy subjects as a first necessary step towards the long-term goal of application the psychophysiological techniques in diagnostics mood and cognitive disorders. The second aim was to establish an easily applicable set of tests for evaluating emotional and memory processes by non-invasive psychophysiological methods. EEG, GSR, and eye-tracking data from 100 participants without any neurological or psychiatric disorders were obtained during watching affective pictures and performing memory tests. The spectral powers were computed for each 500 ms of the stimuli in theta, alpha, beta1, beta2 and beta3 bands in 12 areas of the brain. Lower alpha and higher beta3 power was related to higher emotional intensity. Negative emotions were distinguished in spatio-temporal changes of beta1 power and positive emotions showed higher beta3 power in right temporal region. Memory encoding showed higher alpha power. Lower theta and higher alpha power in central regions and overall increase of beta bands were observed during successful memory retrieval. A summary of spatio-temporal spectral correlates to emotional and memory processes was provided by this work. Key words: Electroencephalography, electrodermal activity, psychophysiology,...

Emotiv EPOC is a low-cost consumer headset capable of acquiring a raw EEG signal. The thesis evaluates its usage for an acquisition of research event-related potentials. A controlled laboratory experiment was performed with an objective of isolating the Bereitschaftspotential (Readiness Potential) and other movement-related potentials and comparing the results with the results of the previous research. The possibility of measuring the potential with Emotiv EPOC was not confirmed, most probably due to procedural issues during the experiment, however, further analysis of the data suggests its presence. Other outcomes of the research include qualitative findings about the headset, mainly its hardware construction, and testing feedback of EEGLab, an open source toolbox for EEG processing and visualization.

This work describes basics of electroencaphalography, measuring electroencaphalography signals, their processing and evaluation. There is discussed method of topography mapping of brain activity called brainmapping. The practical part contains description of design aplication in Matlab.

Title of thesis: Clinical Effectiveness of the Schultz Autogenic Training on the Electrical Activity of the Brain Objectives: The thesis aims to analyze the impact of Schultz autogenic training on brain activity evaluated using EEG Course of action: To obtain the data, an experimental group containing 11 participants aged 20-30, disregarding gender, was created. Participants practiced Schultz autogenic training using the identical audio record once a day during the course of nine weeks. Upon completion of the training, all participants were subjected to one-off measurement by the Nicolet EEG instrument. Brain activity was measured before, during and after the training. Obtained EEG data were processed with NeuroGuide software using coherence analysis and fast Fourier transform. Coherence analysis provided charts mapping the electrical activity of Brodmann areas during the course of all three stages and fast Fourier transform yielded data of performance ratio between theta and alpha frequencies, so called T/A index. Performance ratio of the T/A index was subject to Student's paired t-test in order to draw final conclusion. T/A results show changes in the representation of alpha and theta waves during all measurements. Results: The results of the thesis were used to verify the veracity of stated...

Cognitive processes associated with spatial orientation can use different reference frames: egocentric, centered on observer and allocentric, centered on objects in the environment. In this thesis, we use EEG to investigate the dynamics of brain processes accompanying spatial orientation based on these reference frames. Participants were instructed to estimate distances between objects or themselves and objects located in a virtual circular arena; this task was presented in both 2D and 3D displays. Task-related EEG changes were analyzed using a time-frequency analysis and event-related potential analysis of 128-channel EEG recordings. Through time-frequency analysis we found significant power differences in delta, theta, alpha, beta and gamma bands amongst the control, egocentric and allocentric testing conditions. We noted a decrease in alpha power in occipital and parietal regions, while a significantly stronger decrease was observed for the allocentric condition compared to both egocentric and control conditions. A similar pattern was also detectable for the beta band. We also report an increase in theta and delta power in temporal, fronto-temporal and lateral frontal regions that was significantly stronger for the egocentric condition compared to control and, in some electrodes, even...

This master’s thesis deals with issues of the detection of K-complexes in EEG sleep signals. Record from an electroencephalograph is important for non-invasive diagnosis and research of brain activity. The scanned signal is used to examine sleep phases, disturbances, states of consciousness and the effects of various substances. This work follows the automatic detection of K-complexes, because the manual labeling of graphoelements is complicated. Two approaches were used –Stockwell transform and bandpass filtration followed by TKEO operator application. All algorithms were created in the MATLAB R2014a.

This thesis describes recording, processing and classifying brain activity which is being captured by a brain-computer interface (BCI) device manufactured by OpenBCI company. Possibility of use of such a device for controlling an application with brain activity, specifically with thinking of left or right hand movement, is discussed. To solve this task methods of signal processing and machine learning are used. As a result a program that is capable of recording, processing and classifying brain activity using an artificial neural network is created. An average accuracy of classification of synthetic data is 99.156%. An average accuracy of classification of real data is 73.71%.

Presented master's thesis deals with detection of brain wakefulness from scalp EEG data with higher order statistics. Part of the thesis is a description of electroencephalography, from the method of signal generation, sensing, electroencephraphy, EEG signal artifacts, frequency bands of EEG signal to its possible processing. Furthermore, the concept of mental fatigue and the possibility of its detection in the EEG signal is described. Subsequently, the principles of higher statistical methods of PCA and ICA and the specific possibilities of decomposition of EEG signal are described using these methods, from which the method of group spatial-frequency ICA was chosen as a suitable method for selection of partial oscillatory sources in EEG signal. In the next part there is described a method of acquisition of data, a the suggestion of solution with selected method and a description of the implemented algorithm, that was applied to real 256-lead scalp EEG data captured during a block task focused on subject allertnes. The absolute and relative power of the EEG signal was decomposed. From the achieved results, we observe that the fluctuations of the spatial frequency patterns of relative power (especially for theta and alpha bands) significantly more closely correspond with the change of reaction time and the error of the subjects performing the task. These observations appear to be relatively consistent with previously published literature, and the current study shows that spatial frequency ICA is able to blindly isolate space-frequency patterns whose fluctuations are statistically significantly correlated with parameters (reaction time, error rate) directly flowing from the given task.

This thesis deals with questions of scanning electric activity of brain,¬ so-called electroencephalograph (undermentioned EEG), methods of audiovisual stimulation (undermentioned AVS) and a data-measurement processing. Theoretical part of the thesis is engaged in a theory of EEG signal creation, history and even in current methods of purchasing and processing of the EEG signal, theory of AVS and a theory of biofeedback. For measuring EEG signal with or without an application of AVS methods has been used EEG diagnostic device by Alien company. Its attributes are described in the thesis as well. For elaboration and analysis has been created a programme aplication EEG_xhroze00.fig which realizes frequency spectrum analysis using Fast Fourier Transform algorithm (FFT) and another programme aplication brain_mapping.fig for mapping activity of brain using designed algorithm.