| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10345526 | Computer Methods and Programs in Biomedicine | 2014 | 13 Pages |
Abstract
The results allow to face optimistically the feasibility of a patient specific prospective alarming system, based on machine learning techniques by considering the combination of several univariate (single-channel) electroencephalogram features. We envisage that this work will serve as benchmark data that will be of valuable importance for future studies based on the European Epilepsy Database.
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Physical Sciences and Engineering
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Computer Science (General)
Authors
César Alexandre Teixeira, Bruno Direito, Mojtaba Bandarabadi, Michel Le Van Quyen, Mario Valderrama, Bjoern Schelter, Andreas Schulze-Bonhage, Vincent Navarro, Francisco Sales, António Dourado,