抽象的な

Study of Two Common Brain Disorders using Statistical Parameters

R. Kalpana and I. Gnanambal

Seizures are characterized by excessive brain activity or jumpiness in the patient. Usually the patient suffers from excessive shaking of body and moments of blankness. By predicting the on-set, a physician can administer the required drugs and prevent/control the seizure thereby reducing the pain to the patients. EEG is a random process and linear analysis will not provide us with detailed information. Seizures are non-stationary in nature; therefore they are distinguished by anomalies in values of non-linear parameters such as Bi-correlation, Approximate Entropy (ApEn), Hurst Exponent. Statistical measures, time series plots are the basic ways of differentiating the changes in nature of EEG when a seizure has occurred in a subject. This methodology of analysis confirms the occurrence of this event and appropriate measures can be taken to treat the subject. We can define depression as that state of mind when we perceivably become slow in thoughts as well as action. Brain is too entangled in a maze of its own design in this state and it is among those brain disorders that lead to slow electrical activity.