A Review of the Recurrence Based Techniques for Detection of Various Neurological Disorders

Abstract: There are certain neurological disorders like Alzheimer�s disease, epilepsy etc which are characterized by recurring patterns in EEG obtained from the patient. If this recurrence pattern is observed and the degree of repetition can be studied then we can detect the presence of a disease and moreover if the degree of the repetition or recurrence can be detected by any parameter then further the intensity or the stage of the neurological diseases can also be diagnosed. This work mainly focuses on developing the algorithm and then a program using MATLAB so as to detect the seizures occurring in humans. This program will take the EEG signals from the Subject as input and will detect the recurrence patterns in the subject by using the mathematical concept of recurrences. Moreover different schemes of recurrence detection will also be used and the results will be compared so as to find the best of all the recurrence methods. This paper aims at giving the understanding of the synchronization that occurs in various natural and biological phenomenons and paves the way and prepares a ground for utilising this synchronization to detect and diagnose the neurological disorders in humans like epilepsy, alzheimer�s disease etc.

Keywords: EEG Waves, Synchronization Index, Coupling Index, Recurrences.