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...

The use of automatic electrical stimulation in response to early seizure detection has been introduced as a new treatment for intractable epilepsy. For the effective application of this method as a successful treatment, improving the accuracy of the early seizure detection is crucial. In this paper, we proposed the application of a frequency-based algorithm derived from principal component anal...

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...

BACKGROUND Although epilepsy affects most patients with tuberous sclerosis complex (TSC), little is known about the natural history of epilepsy in this genetic disease. METHODS A retrospective chart review of all patients with TSC seen between January 2002 and October 2008. Charts were reviewed for a history of infantile spasms (IS), seizure other than IS, refractory epilepsy, Lennox-Gastaut ...

Epilepsy is a chronic neurological disorder that affects more than 50 million people world wide, characterized by recurrent seizures (World Health Organization [WHO], 2006). An epileptic seizure is a transient occurrence of signs and/or symptoms due to abnormal excessive or synchronous neuronal activity in the brain (Fisher et al., 2005 & Berg et al., 2010). This electrical hyperactivity can ha...

Closed-loop neurostimulation devices that stimulate the brain to treat epileptic seizures have shown great promise in treating more than a third of the 2 million people with epilepsy in the United States alone whose seizures are currently nonresponsive to pharmaceutical treatment. Seizure detection algorithms facilitate responsive therapeutic intervention that is believed to increase the effica...

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 ...