Examination of Multiple Spectral Exponents of Epileptic ECoG Signal

In this paper, the wavelet-based fractal analysis is applied to analyze an electrocorticogram (ECoG) signal recorded from an epilepsy patient. A spectral exponent γ yielded from the wavelet-based fractal analysis is determined from a slope of log 2 var(dm,n)-m graph over an interval of levels. Rather than a single spectral exponent, multiple spectral exponents determined from various intervals of levels corresponding to various ranges of spectral subbands of the ECoG signal are examined. From the computational results, it is observed that the spectral exponents of the ECoG signal estimated from different intervals of levels m exhibit different intriguing characteristics. It is also shown that the spectral exponents of the ECoG signal obtained during epileptic seizure events are significantly different from those of the ECoG signal obtained during non-seizure period. Furthermore, during nonseizure period the spectral exponent of the ECoG signal tends to decrease as the corresponding range of frequencies of subband decreases. On the contrary, for almost all spectral subbands the spectral exponents of the ECoG signal tend to be comparable except the lowest frequency subband.