Fractal Methods and Power Spectral Density as Means to Explore EEG Patterns in Patients Undertaking Mental Tasks

Fractal and Fractional

Carlos Alberto Valentim¹  Sergio Adriani David²  Claudio Marcio Cassela Inacio² 

[1] Department of Biosystems Engineering, University of São Paulo, Av. Duque de Caxias Norte 225, Pirassununga 13635-900, SP, Brazil;Institute of Mathematics and Computer Science, University of São Paulo, Av. Trabalhador São-Carlense 400, São Carlos 13566-590, SP, Brazil;

关键词: EEG signals;    fractal dimension;    power spectral density;    detrended fluctuation analysis;    hurst;   

DOI  :  10.3390/fractalfract5040225

来源: DOAJ

【 摘 要 】

Brain electrical activity recorded as electroencephalogram data provides relevant information that can contribute to a better understanding of pathologies and human behaviour. This study explores extant electroencephalogram (EEG) signals in search of patterns that could differentiate subjects undertaking mental tasks and reveals insights on said data. We estimated the power spectral density of the signals and found that the subjects showed stronger gamma brain waves during activity while presenting alpha waves at rest. We also found that subjects who performed better in those tasks seemed to present less power density in high-frequency ranges, which could imply decreased brain activity during tasks. In a time-domain analysis, we used Hall–Wood and Robust–Genton estimators along with the Hurst exponent by means of a detrented fluctuation analysis and found that the first two fractal measures are capable of better differentiating signals between the rest and activity datasets. The statistical results indicated that the brain region corresponding to Fp channels might be more suitable for analysing EEG data from patients conducting arithmetic tasks. In summary, both frequency- and time-based methods employed in the study provided useful insights and should be preferably used together in EEG analysis.

【 授权许可】

Unknown