The unpredictability of seizures is a central problem for all patients suffering from uncontrolled epilepsy. Recently, numerous methods have been suggested that claim to predict from the EEG the onset of epileptic seizures. In parallel, new therapeutic devices are in development that could control upcoming seizures provided that their onset is known in advance. A reliable clinical application c...

In this era, big data applications including biomedical are becoming attractive as the data generation and storage is increased in the last years. The big data processing to extract knowledge becomes challenging since the data mining techniques are not adapted to the new requirements. In this study, we analyse the EEG signals for epileptic seizure detection in the big data scenario using Rotati...

A Matlab®-based software package, EPILAB, was developed for supporting researchers in performing studies on the prediction of epileptic seizures. It provides an intuitive and convenient graphical user interface. Fundamental concepts that are crucial for epileptic seizure prediction studies were implemented. This includes, for example, the development and statistical validation of prediction met...

This paper deals with the design of low power low noise neural signal amplifier for Epileptic Seizure Prediction. The advent of Micro-electro Arrays has driven the need for implantable electronic circuitry to detect those Extracellular neural signals (ENG). We proposed a preamplifier of fully differential Low Noise Amplifier (LNA) with gm boosting in order to enhance the gain as well as reduce ...

News and Events Elite Graduate Program " Neurosciences " – Bernstein Centers at the " Germany in Japan " Initiative – Bernstein Award 2006 – Upcoming Events BCCN Newsletter Scientists at the BCCN develop a procedure to evaluate algorithms that predict epileptic seizures Epilepsy is a widespread neurological disease that is characterized by the spontaneous and hitherto unpredictable incidence of...

A comprehensive research of Electroencephalography (EEG) is carried out on Empirical Mode Decomposition (EMD) and Discrete Wavelet Transform (DWT) domains. In this scenario, the hybrid feature extraction is performed by utilizing entropy features like Shannon entropy, log-energy entropy and Renyi entropy. Generally, the entropy measures are effective in evaluation of non-linear interrelation an...

E PILEPSY is the most common neurological disorder after stroke, and affects almost 60 million people worldwide. Medications control seizures in only 2/3 of those affected, and another 7%–8% are potentially curable by surgery. This leaves fully 25%, or 15 million people whose seizures cannot be controlled by any available therapy. Over the past ten years engineers and quantitative scientists ha...