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Full-Text Articles in Engineering

An Investigation Into The Development Of A Low Cost, Easy To Use Seizure Analysis Tool., Cody Dean Dec 2020

An Investigation Into The Development Of A Low Cost, Easy To Use Seizure Analysis Tool., Cody Dean

Masters Theses

The need for collaborating and sharing data and research between doctors, researchers, universities and patients has never been more necessary. We are seeing firsthand how a deadly virus can completely devastate the world in a matter of months and being able to react quickly is the top priority. Open source tools are making it possible to share research and learnings about viruses like COVID-19 across countries, industries, and universities and these tools and philosophies extend across all areas of medical research.

The amount of data that is being collected within the medical industry is increasing at an exponential rate and …


Differentiating Epileptic From Psychogenic Nonepileptic Eeg Signals Using Time Frequency And Information Theoretic Measures Of Connectivity, Sarah Barnes Dec 2019

Differentiating Epileptic From Psychogenic Nonepileptic Eeg Signals Using Time Frequency And Information Theoretic Measures Of Connectivity, Sarah Barnes

Masters Theses

Differentiating psychogenic nonepileptic seizures from epileptic seizures is a difficult task that requires timely recording of psychogenic events using video electroencephalography (EEG). Interpretation of video EEG to distinguish epileptic features from signal artifacts is error prone and can lead to misdiagnosis of psychogenic seizures as epileptic seizures resulting in undue stress and ineffective treatment with antiepileptic drugs. In this study, an automated surface EEG analysis was implemented to investigate differences between patients classified as having psychogenic or epileptic seizures. Surface EEG signals were grouped corresponding to the anatomical lobes of the brain (frontal, parietal, temporal, and occipital) and central coronal …


Identification Of The Seizure Onset Zone By Auto-Regressive Model Residual Modulation Applied To Intracranial Eeg And Its Correlation To Channels With High Preponderances Of Detected Hfos, Allison L. Rogutich Aug 2018

Identification Of The Seizure Onset Zone By Auto-Regressive Model Residual Modulation Applied To Intracranial Eeg And Its Correlation To Channels With High Preponderances Of Detected Hfos, Allison L. Rogutich

Masters Theses

The objective of this thesis was to examine the ability of the Autoregressive Model Residual Modulation (ARRm) method to identify the Seizure Onset Zone (SOZ) in intracranial electroencephalogram (iEEG) of patients with refractory epilepsy. Patients who have not become seizure free after multiple trials of antiepileptic drugs (AEDs) may seek treatment through epilepsy surgery. Cortical electrodes are implanted directly on the cerebral cortex, then iEEG is collected. A specialized neurologist reviews the iEEG, then in consultation with the neurosurgeon, the SOZ is determined and areas of the brain may be chosen for resection. The success rate of epilepsy surgery varies, …


Human Intracranial High Frequency Oscillation Detection Using Time Frequency Analysis And Its Relation To The Seizure Onset Zone, Riazul Islam Aug 2015

Human Intracranial High Frequency Oscillation Detection Using Time Frequency Analysis And Its Relation To The Seizure Onset Zone, Riazul Islam

Masters Theses

One third of the patients diagnosed with focal epilepsy do not respond to antiepileptic drugs. For these patients the possible diagnosis options to give seizure freedom or at least reduce seizure frequencies significantly would be surgical resection or seizure interrupting implantable devices. The success of these procedures depends on accurate detection of the region causing seizure also known as epileptic zone. This requires detail pre-surgical evaluation including Invasive Video Electroencephalographic Monitoring (IVEM). The resulting great volume of intracranial Electroencephalography (iEEG) signal is visually examined by an expert epileptologist which can be time consuming, extremely complex, and not always effective. We …


Automated Classification Of Eeg Signals Using Component Analysis And Support Vector Machines, Priya Balasubramanian Dec 2014

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 Apr 2014

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 …