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540:691 SEMINAR IN INDUSTRIAL & SYSTEMS ENGINEERING |
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EEG
Signal Processing as a Physiological Marker Dr.
George A. Ghacibeh Abstract: Epilepsy is a chronic neurological disease characterized by a tendency to have recurrent seizures. A seizure is a self-limited episode of neurological symptoms caused by excessive electrical activity of brain cells. Treatment of seizures depends on the correct diagnosis. The main diagnostic test used by clinicians is the Electroencephalogram (EEG), which measures the electrical activity generated by large populations of neurons. When there is a question about the diagnosis of seizures, long-term EEG monitoring is performed over several days until a seizure is recorded, to determine the exact nature of the disease. Many patients are misdiagnosed as having seizures when their episodes are non-epileptic, caused by psychological, cardiac or metabolic disorders. In addition, the majority of patients with epilepsy are treated with antiepileptic drugs (AED), with about 70% achieving control of their seizures, however, many suffering side effects. AED treatment is performed using a “trial and error” method, the error being either recurrent seizures or intolerable side effects. Many patients with epilepsy are treated with higher dosages of AED than needed, resulting in unnecessary side effects. In contrast, many patients are under-treated for long periods of time, running the risk of seizure recurrence. Therefore, there is a need to develop a reliable biological marker that would help with the precise diagnosis of seizures and would also help assess the adequacy of a given AED regimen. AEDs have different and multiple mechanisms of action, but they all result in reduction in seizure frequency. This is probably achieved by influencing the tendency of cortical neurons and networks to engage in seizure activity. The Electroencephalogram (EEG) measures the electrical activity of cortical neurons and may serve as a potential physiological marker for epilepsy in general and for the assessment of AED efficacy and toxicity. Nonlinear EEG analyses use complex mathematical methods to analyze the dynamical properties of the EEG. There is evidence that dynamical EEG analysis can provide quantitative information associated with the epileptic state and correlate with antiepileptic drug levels and cognitive function. The overall aim of this research is to develop a quantitative EEG measure that would serve as physiological marker to help diagnose epileptic seizures and distinguish them from non-epileptic events and that would optimize AED therapy and minimize side effects, using nonlinear dynamical EEG analysis.
*Refreshments will be served in the IE lounge area at 4:30 prior to the seminar. Speaker is hosted by Wanpracha Chaovalitwongse Tel:
732-445-5469, Email: wchaoval@rci.rutgers.edu
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