EEG signal analysis using different clustering techniques

Abstract

Electroencephalogram (EEG) is a test used to detect neurological disorders by checking the electrical activity in the brain. EEG is done to check problems related to the electrical activity of brain and its disorders such as epilepsy and types of seizures occurring, sleep disorders such as narcolepsy, encephalitis, brain tumor, Stroke, Dementia, etc. EEG may also be used to check out if a person is brain dead in persistent coma. The electrical activity of brain is checked with the help of electrodes attached to the scalp and recorded in computer. With increasing database performance of K-Means, and FCM is not efficient. In this paper we propose spatial clustering algorithm for EEG signals to improve the efficiency.