FRACTAL INDEX ANALYSIS OF HUMAN ELECTROENCEPHALOGRAM SIGNALS

摘要

A system and method for Multifractal-Detrended Fluctuation Analysis (MF-DFA) on digitized Human EEG signals is presented. A list of Hurst exponents, or Hurst exponent spectrum (“h” values) are generated, and multifractal singularity spectrum indices (“D(h)” values) produce a graph that approximates an inverted parabola. The output multifractal DFA spectrum is able to represent key features of the internal neuronal dynamics for the cortical neurons underlying the scalp-placed electrode which records the signals.