Analysing Gamma Frequency Components in EEG Signals: A Comprehensive Extraction Approach
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Abstract
Gamma band activity is a high-frequency (30-100 Hz) oscillation of the electroencephalogram (EEG) that has been linked to a variety of cognitive processes including attention, memory and learning. However, extracting gamma band activity from EEG data can be challenging due to the relatively low signal-to-noise ratio of gamma band signals and the presence of other frequency bands such as beta and alpha. In this paper, we present a method for extracting gamma band activity from EEG data. We evaluated our method on a dataset of EEG data recorded from dyslexic patients. We found that our method was able to successfully extract gamma band activity from the EEG data. The extracted gamma band activity was significantly correlated with the subjects' performance on the visual attention task. Our results suggest that our method is an easy and straightforward approach for extracting gamma band activity from EEG data. This could be used to study the neural basis of cognitive processes in a variety of research settings.
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