Title :
Reexamination of characteristic of spectral exponent of epileptic EEGs corresponding to levels in wavelet-based fractal analysis
Author :
Janjarasjitt, Suparerk
Author_Institution :
Dept. of Electr. & Electron. Eng., Ubon Ratchathani Univ., Ubon Ratchathani, Thailand
Abstract :
Recently, the characteristics of epileptic EEG data have been examined by using the wavelet-based fractal analysis. It was observed that epileptic EEG data may be associated with multiple spectral exponents. In this study, the characteristic of spectral exponents of epileptic EEG data determined from various intervals of levels (or ranges of spectral subbands) is reexamined by applying the wavelet-based fractal analysis to EEG data of epilepsy patients. From the computational results, it is confirmed that the spectral exponent of epileptic EEG data varies corresponding to an interval of levels from which it is determined. Also, it is shown that the spectral exponents of epileptic EEG data obtained during non-seizure period and seizure activity determined from high frequency (10.85-21.70Hz) subband and low frequency (1.36-10.85Hz and 2.71-21.70Hz) subbands are substantially different.
Keywords :
brain; electroencephalography; fractals; medical disorders; wavelet transforms; computational model; epilepsy patients; epileptic EEG data; high-frequency subband; multiple spectral exponents; nonseizure period activity; wavelet-based fractal analysis; Brain modeling; Electroencephalography; Gold; Manganese; Muscles; electroencephalogram; epilepsy; seizure; spectral exponent; wavelet transform;
Conference_Titel :
Biomedical Engineering International Conference (BMEiCON), 2014 7th
Conference_Location :
Fukuoka
DOI :
10.1109/BMEiCON.2014.7017370