Characterization of EEG signal changes via Itakura distance

Clinical assessment of neurological system would be greatly facilitated by interpretation of disease- or injury-related changes in electroencephalogram (EEG) signals. Under the assumption that EEG signal can be modeled as an autoregressive (AR) process, Itakura distance is used to measure the similarity of the EEG signals obtained during various phases of the experimental study. The effectiveness of the Itakura distance is demonstrated through its ability to distinguish hypoxia and asphysia as well as to predict recovery following the injury