Critical Review of Epileptic Prediction Model Using Eeg

Epilepsy is a condition that affects the brain and causes repeated seizures. Epilepsy is the second most common neurological disorder, affecting 0.6–0.8% of the world’s population. In this neurological disorder, abnormal activity of the brain causes seizures, the nature of which tend to be sudden. The cells in the brain, known as neurons, conduct electrical signals and communicate with each other in the brain using chemical messengers. During a seizure, there are abnormal bursts of neurons firing off electrical impulses, which can cause the brain and body to behave strangely. The severity of seizures can differ from person to person. For most people with epilepsy, treatment with medications called anti-epileptic drugs (AEDs) is recommended. These medications cannot cure epilepsy, but they are often very effective in controlling seizures. The unpredictable nature of seizures poses risks for the individual with epilepsy. It is necessary to find more effective ways of preventing seizures for such patients. The early detection of oncoming seizures, before their actual onset, can facilitate timely intervention and hence minimize these risks. Before a seizure happens, a number of characteristic, clinical symptoms occur that is used to identify the pre-seizure state by monitoring brain activity through the electroencephalogram (EEG). In this paper, we present an extensive review of the significant researches associated with the prediction of Epileptic Seizures using EEG signals. In addition with different Seizure prediction method.