Engineering Commons^™

Automated Classification Of Eeg Signals Using Component Analysis And Support Vector Machines, Priya Balasubramanian

Masters Theses

Epileptic seizures are characterized by abnormal electrical activity occurring in the brain. EEG records the seizures demonstrating changes in signal morphology. These signal characteristics, however, differ between patients as well as between different seizures in the same patient. Epilepsy is managed with anti-epileptic medications but in some extreme cases surgery might be necessary. Non-invasive surface electrode EEG measurement gives an estimate of the seizure onset but more invasive intra-cranial electrocorticogram (ECoG) are required at times for precise localization of the epileptogenic zone.

The epileptogenic zone can be described as the cortical area targeted for resection to render the patient symptom …

A Quantitative Tool For Identifying The Epileptogenic Zone Using Network Connectivity Analysis, James Michael Gurisko

Masters Theses

Approximately one-third of patients diagnosed with focal epilepsy do not respond to medication and may be candidates for surgery to remove epileptogenic tissue known as the epileptogenic zone. A detailed pre-surgical evaluation is required and often includes invasive video electroencephalographic monitoring (IVEM) using intracranial surface and depth electrodes, and a camera. The resulting large pools of electrocorticorticographic (ECoG) data are manually analyzed by an expert epileptologist to determine epileptic events. The process is time consuming and prone to human error. This thesis investigates the use of measures to identify the causal relationship between ECoG signals during propagation of a seizure …