Wavelet entropy method for EEG analysis: application to global brain injury

Abstract

A novel method, "wavelet entropy," is presented for the analysis of EEG signals recorded during injury and recovery following global cerebral ischemia. The EEG is recorded from rodent brains in a controlled experimental brain injury model by hypoxic-ischemic cardiac arrest. Wavelet analysis is used to decompose the EEG into standard clinical subbands. Entropy is then computed using these wavelet coefficients. The wavelet entropy helps segment periods of bursting in EEG signals. The residual entropy of the wavelet coefficients is also computed. It reflects the degree of synchronization of the brain rhythm generators.