Analysis and visualization of human electroencephalograms seen as fractal time series

The paper presents a novel technique of nonlinear spectral analysis. This technique is based on the concept of generalized entropy of a given probability distribution, known as the Renyi entropy. This concept allows defining generalized fractal dimension of encephalogram (EEG) and determining fractal spectra of encephalographic signals. These spectra contain information of both frequency and amplitude characteristics of EEG and can be used together with well-accepted techniques of EEG analysis as an enhancement of the latter. Powered by volume visualization of the brain activity, the method provides new clues for understanding the mental processes in humans.