Diagnosis of epilepsy — A systematic review

Epilepsy is the most common chronical disorder affecting nearly 50 million people worldwide and is associated with periodic loss of consciousness characterized by recurrent seizures with the abnormal electrical activity of the brain. According to Bangalore Urban Rural Neuro-epidemiological Survey (BURNS) approximately 51502 urban and 51055 rural people are affected with epilepsy in Bangalore. The prime requirement for successful predetermination and diagnosis of epilepsy is the selection of optimal treatment to benefit the patients who need extreme care. Recently, most of the research has been initiated to prevent and diagnose the epilepsy. In this paper detection of epilepsy based on both signal and image processing have been reviewed along with the comparison of performance of different feature extraction methods and classifiers. Multi model approaches have also been discussed which improves the specificity of the system reduces fault detection and retrieves more information about disorder in the brain.