Kvantifikační analýza metod fNIRS a EEG pro studium variabilních podnětů

Abstract

This Master’s thesis focuses on the quantitative analysis of brain activity using electroencephalography (EEG) and functional near–infrared spectroscopy (fNIRS) during exposure to variable stimuli, specifically meditation and arousal. The aim was to identify characteristic changes in EEG and fNIRS signals across different mental states and to assess the potential for their combined interpretation. Various metrics were extracted from the signals, including power spectral density, beta/alpha ratio, entropy, correlation coefficients, root mean square error, and others. The signals were analyzed in time, frequency, and statistical domains. The results revealed significant differences between the states, particularly in the frontal and central cortex areas. Higher signal complexity was observed during meditation, while increased activation was evident during stress. Correlations between EEG and fNIRS metrics further indicated a functional link between the brain’s electrical and hemodynamic activity. The findings of this study support the use of a multimodal approach in the assessment of psychophysiological states and highlight the potential of EEG and fNIRS as complementary methods for detecting changes in cognitive and emotional load.