We compare the performance of three support vector machine (SVM) types: weighted SVM, one-class SVM and support vector data description (SVDD) for the application of seizure detection in an animal model of chronic epilepsy. Large EEG datasets (273 h and 91 h respectively, with a sampling rate of 1 kHz) from two groups of rats with chronic epilepsy were used in this study. For each of these EEG ...

Epilepsy is one of the common neurological disorders characterized by a sudden and recurrent malfunction of the brain that is termed “seizure”, affecting over 50 million individuals worldwide. The Electroencephalogram (EEG) is the most influential technique in detection of epileptic seizures. In recent years, many research works have been devoted to the detection of epileptic seizures based on ...

OBJECTIVE Around 1% of the world's population is affected by epilepsy, and nearly 25% of patients cannot be treated effectively by available therapies. The presence of closed-loop seizure-triggered stimulation provides a promising solution for these patients. Realization of fast, accurate, and energy-efficient seizure detection is the key to such implants. In this study, we propose a two-stage ...

Background: Electroencephalography (EEG) is an electrophysiological observing strategy to record the electrical activity of brain which used in a seizure disorder, organicity, and psychiatric conditions. In spite overwhelming burden epilepsy Bangladesh, there remains relative scarcity neurophysiology services restricted distributed information on electroencephalography highlights among populati...

During the colloquium on drug-resistant epilepsy (DRE) at National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore on August 16-18, 2013, a number of presentations were made on the surgically remediable lesional epilepsy syndromes, presurgical evaluation, surgical techniques, neuropathology of drug resistance focal epilepsy and surgical outcome. This pictorial essay with the i...

Epilepsy is the most common brain diseases that cause many problems in the daily life of the patient. In most attempts to automatic detection, the attack used an EEG. In this paper, The complete data set consists of five sets recorded from normal and epileptic patients. Each set containing 100 single-channel EEG segments. Here we used first and last sets (A and E). Set A consisted of segments r...

The role of the inter-ictal EEG in predicting seizure relapse after antiepileptic drug withdrawal (AED-W) is unclear. A prospective study on AED-W is in progress. This trial includes routine and sleep EEG recordings every 3 and 6 months, respectively, at each step of the drug discontinuation and periodically during follow-up. Data obtained for 136 patients (mean age 23.2 years; 63 with Idiopath...