Representation and Analysis of Biomedical Signals using Fourier Decomposition Method

Abstract

Due to rapid growth in the arena of health care sectors, various non-invasive tools, for in- stance electroencephalogram (EEG), electrocardiogram (ECG) and positron emission tomog- raphy (PET) have established their signi_cance in the analysis and interpretation of various health issues such as brain disorders, heart diseases, sleep disorders and alcoholism identi_- cation. Epilepsy is one of the most prevalent neurological disorders in humans characterized by transient and hyper-synchronization movement of neuronal discharges in the brain cortex. Clinical information related to brain disorders is complex and multi-dimensional, and such in- formation may produce an amalgamation of multiple research problems. Due to its low cost, high temporal resolution and non-invasive nature, EEG is the most frequently used technique for the analysis of various brain disorders. The detection of such abnormalities is usually performed by trained professionals using continuous monitoring of EEG recording, which is a tedious and challenging task that may produce inaccurate diagnosis results due to fatigue of trained experts. Therefore, numerous e_orts have been made by the researchers towards the automatic detection of epileptic seizures.