STUDY OF TRANSFER ENTROPY ON EPILEPTIC EEG SIGNALS
Open Access
- Author:
- Kale, Poojitha
- Graduate Program:
- Electrical Engineering
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- February 21, 2019
- Committee Members:
- Aylin Yener, Thesis Advisor/Co-Advisor
Mohamed Khaled Almekkawy, Thesis Advisor/Co-Advisor - Keywords:
- electroencephalogram
Transfer entropy
Non-linear
Epilepsy - Abstract:
- Epilepsy is the fourth largest neurological disorder characterized by recurrent unprovoked seizures. The usual brain activity is disturbed for the duration of the seizure which can last a few seconds up to a few minutes. About one-third of the people suffer from medically refractory seizures. This means that medication alone cannot make the patient seizure free. These patients are often evaluated for surgery where the focus of the epileptogenic zones (EZs) are resected. Identification of these EZs is made easy by subjecting the patients to an invasive EEG monitoring method, where multiple intracerebral depth electrodes are used to capture the electrical activity of the brain. In this thesis, an alternate method named Transfer Entropy (TE) is proposed over the standard method of evaluating these signals by visually identifying the changes in the EEG signal. This method accurately accounts for non-linearity and dynamic interactions between the systems involved. By applying this method to the EEG data of four epileptic patients, the location of EZs for each patient was identified. In addition to this, investigation on the changes in the TE calculations by changing parameters such as the bin size and the order of the Markov processes has been studied. Computation and comparison of both the linear (Correlation) and non-linear (TE) calculations have been shown to show why this particular method proves to be more useful.