Study On Kolmogorov Complexity And Approximate Entropy Of Epileptic Electroencephalogram

Brain is the most complicated system in the world. Consciousness is still a mystery to people. With the development of non-invasive measurements, such as electroencephalography (EEG), megnetoencephalography (MEG), functional magnetic resonance imagine (fMRI), and positron emission tomography (PET), studying the consciousness objectively and systematically is approachable.Electroencephalogram (EEG) records the enlarged electoral activities of cortical neuron directly from the surface of scalp; it is an important guideline for identifying and understanding functions of brain activities.Many recent studies have demonstrated the presence of deterministic non-linear or chaotic behavior in EEG signals and cortical neurons activity. Non-linear analysis of the EEG provides a new possibility for studying the dynamical changes in cortical networks related to physiology and pathology.There are two main problems yet to be solved. We now need quite long EEG data in calculating the indexes of non-linear dynamic, but EEG signals are instable; besides, over-long data are hard to be calculated. Another problem is how to apply the studies in practice. There are few studies about application of non-linear analysis of EEG at present, especially in the study of epilepsy.Two new dynamical approaches of non-linear, Kolmogorov Complexity (Kc)...