Parameters analyzed of Higuchi's fractal dimension for EEG brain signals

Due to the stochastic nature of EEG signals, various nonlinear patterns and methods have been applied in order to obtain characteristic understanding of their dynamic behavior [6]. The Fractal Dimension (FD) is an appropriate tool to analyzed EEG signals and can be calculated by means of the Higuchi...

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Bibliographic Details
Published in2015 Signal Processing Symposium (SPSympo) pp. 1 - 5
Main Authors Flores Vega, Christian, Noel, Julien
Format Conference Proceeding
LanguageEnglish
Published Warsaw University of Technology 01.06.2015
Subjects
cognitive task
EEG signals
Electrodes
Electroencephalography
Fractal Dimension
Fractals
Higuchi's method
Prediction algorithms
Signal to noise ratio
Time series analysis
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Summary:Due to the stochastic nature of EEG signals, various nonlinear patterns and methods have been applied in order to obtain characteristic understanding of their dynamic behavior [6]. The Fractal Dimension (FD) is an appropriate tool to analyzed EEG signals and can be calculated by means of the Higuchi's algorithm. Nevertheless, this algorithm depends of the k parameter to improve the speed of calculation. The aim of this work is to analyze the sensitivity of the k parameter due to segmentation, overlap, and noise over a signal. After that, with a better k parameter we applied the FD on EEG brain signals recorded while subjects were executing cognitive task. To analyze the statistical differences for each cognitive mental task, the hypothesis Wilcoxon signed-rank test was applied. The results for all tested brain bands used in this study reported a statistical difference (p <; 0.05) in 9 out of 10 pairs of mental tasks. The proposed approach reported is a good tool for cognitive tasks discrimination. We have also determine better k parameter for different conditions therefore these results can be used for future studies.
DOI:10.1109/SPS.2015.7168285