Epilepsy is one of the world's most common neurological diseases. Reliable early prediction and warning seizures can provide timely treatment for patients with epilepsy, improve their quality life. Compared hand-designed methods, an automatic model that process original electroencephalogram (EEG) signals directly take into account leads optimization problem needed. In this paper, we proposed en...

This study was undertaken to observe the effect of acute stress on seizure occurrence in chronic period of epileptic model rats. Lithium-pilocarpine (LiCl-PILO)-induced epileptic rat model was constructed. At the spontaneous recurrent seizure period, acute stress stimulations such as cat's urine and foot electrical shock were applied to observe the behavioral changes and seizure occurrence. The...

Epilepsy is a common neurological disorder affecting more than 1.5 percent worldwide. Twenty percent of epilepsies are drug resistant. Therefore, early detection of prediction of epileptic seizures is of prime significance to decrease the burdens of the disease. There is strong evidence indicating seizures develop minutes to hours before clinical onset. This change is based on quantitative stud...

Epilepsy is one of the most common neurological disorders that greatly impair patients’ daily lives. A classifier for automated epileptic EEG detection and patient monitoring can be very important for epilepsy diagnosis and patients’ quality of life, especially for rural areas and developing countries where medical resources are limited. This paper describes our development of an accurate and f...

Around 0.6-0.8% of the world’s population is affected by a re-current neurological disorder of epilepsy. Second only to stroke, epileptic seizures interrupt lives of 50 million people. The sudden and seemingly unpredictable nature of seizures is one of the most defeating facts of epilepsy. The ability to predict a rising seizure reliably can mitigate the severity of the disorder and open up new...

Epileptic seizure detection in a large database of Electroencephalography (EEG) signals needs to be a time constrained process for real-time analysis. Epileptic seizure detection algorithms are designed to obtain and analyze a group of neural signals and recognize the presence of seizure occurrence. The computational cost of the algorithms should be minimized to reduce the processing time and m...

Epilepsy can be referred to as a neurological disorder, categorized by intractable seizures with serious consequences. To forecast such seizures, Electroencephalogram (EEG) datasets should gathered continuously. EEG signals were recorded using numerous electrodes fixed on the scalp that cannot worn patients Neurostimulators intervene in advance and ignore seizure rate. Its productivity is incre...