Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 9 of 9 for “"Seizure prediction"”.
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Seizure prediction and control in epilepsy
… two decades in the attempt to forecast epileptic seizure on the basis of intracranial and scalp EEG. Past research could reveal some value of linear and nonlinear algorithms to detect EEG features changing over different phases of the epileptic cycle. However, their exact value for seizure …
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Prediction of canine epilepsy
Seizure prediction is a problem in biomedical science which now is possible to solve with machine learning methods. A seizure prediction system has the power to assist those affected by epilepsy in better managing their medication, daily activities and improving the quality of life. Usage of …
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An Energy-Efficient Spiking CNN Implementation for Cross-Patient Epileptic Seizure Detection
… efficient strategy for automatic cross-patient seizure detection using spatio temporal features learned from multichannel electroencephalogram (EEG) time-series data. In this approach, we utilize an algorithm that seeks to capture spectral, temporal, and spatial information in order to achieve …
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High frequency activity preceding epileptic seizures
… (>100 Hz, HFA) is suggested to be related to seizure genesis, but the mechanism of the HFA is not clear. In the present work HFAs and epileptic features including electrographic seizures (trains of hypersynchronous population spikes lasting ~46 sec) and interictal discharges (abrupt potential …
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A Hidden Markov Factor Analysis Framework for Seizure Detection in Epilepsy Patients
… is the gold-standard for recording epileptic seizures and assisting in the diagnosis and treatment of patients with epilepsy. Detection of seizure from the recorded EEG is a laborious, time consuming and expensive task. In this study, we propose an automated seizure detection framework to …
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Simple linear classifiers via discrete optimization : learning certifiably optimal scoring systems for decision-making and risk assessment
… classification models that let users make quick predictions by adding, subtracting, and multiplying a few small numbers. These models are widely used in applications where humans have traditionally made decisions because they are easy to understand and validate. In spite of extensive deployment, …
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Epileptic Seizure Detection And Prediction From Electroencephalogram Using Neuro-Fuzzy Algorithms
… approaches based on fuzzy logic in epileptic seizure detection and prediction from Electroencephalogram (EEG). The fuzzy rule-based algorithms were developed with the aim to improve quality of life of epilepsy patients by utilizing intelligent methods. An adaptive fuzzy logic system was …
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Computational Approaches To Epilepsy: Graph Networks For Localization And Multi-Model Approach For Prediction
… characterized by a lack of response to antiseizure medications. For these individuals, the primary remaining treatments are surgical intervention or neuromodulation. The success of these interventions depends mainly on solving two critical challenges: first, precisely localizing the seizure …
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Advances in epileptic seizure onset prediction in the EEG with ICA and phase synchronization
Seizure onset prediction in epilepsy is a challenge which is under investigation using many and varied signal processing techniques, across the world. This research thesis contributes to the advancement of digital signal analysis of neurophysiological signals of epileptic patients. It has been …