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...

Great effort has been made toward defining and characterizing the pre-ictal state. Many studies have pursued the idea that there are recognizable electrographic (EEG-based) features which occur before overt clinical seizure activity. However, development of reliable EEG-based seizure detection and prediction algorithms has been difficult. In this review, we discuss the concepts of seizure detec...

OBJECTIVE This study discusses an appropriate framework to measure system performance for the task of neonatal seizure detection using EEG. The framework is used to present an extended overview of a multi-channel patient-independent neonatal seizure detection system based on the Support Vector Machine (SVM) classifier. METHODS The appropriate framework for performance assessment of neonatal s...

For patients with medically intractable epilepsy, there have been few effective alternatives to resective surgery, a destructive, irreversible treatment. A strategy receiving increased attention is using interictal spike patterns and continuous EEG measurements from epileptic patients to predict and ultimately control seizure activity via chemical or electrical control systems. This work compar...

Detecting seizure using brain neuroactivations recorded by intracranial electroencephalogram (iEEG) has been widely used for monitoring, diagnosing, and closed-loop therapy of epileptic patients, however, computational efficiency gains are needed if state-of-the-art methods are to be implemented in implanted devices. We present a novel method for automatic seizure detection based on iEEG data t...

PURPOSE Near infrared spectroscopy (NIRS) has proved useful in measuring significant hemodynamic changes in the brain during epileptic seizures. The advance of NIRS-technology into wireless and portable devices raises the possibility of using the NIRS-technology for portable seizure detection. METHODS This study used NIRS to measure changes in oxygenated (HbO), deoxygenated (HbR), and total h...

The objective is to develop a non-invasive automatic method for detection of epileptic seizures with motor manifestations. Ten healthy subjects who simulated seizures and one patient participated in the study. Surface electromyography (sEMG) and motion sensor features were extracted as energy measures of reconstructed sub-bands from the discrete wavelet transformation (DWT) and the wavelet pack...

Automated methods of neonatal EEG seizure detection attempt to highlight the evolving, stereotypical, pseudo-periodic, nature of EEG seizure while rejecting the nonstationary, modulated, coloured stochastic background in the presence of various EEG artefacts. An important aspect of neonatal seizure detection is, therefore, the accurate representation and detection of pseudo-periodicity in the n...