Anzeige
Erschienen in:
2019 | OriginalPaper | Buchkapitel
EEG Signal Processing: Applying Deep Learning Methods to Identify and Classify Epilepsy Episodes
verfasst von : George Suciu, Maria-Cristina Dițu
Erschienen in: Future Access Enablers for Ubiquitous and Intelligent Infrastructures
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
Epilepsy is a chronic disease characterized by a deviation from the normal electrical activity of the brain leading to seizures caused by nerve impulses discharge. It is currently considered the fourth global neurological problem, being overcome only by diseases such as strokes. Moreover, according to the World Health Organization, nearly 50 million people suffer from epilepsy, with approximately 2.4 million patients annually diagnosed. It is worth mentioning that the elderly and children are the most exposed categories, but if the situation is considered, one of 26 people is likely to develop this condition at a point in life.
Through three gates, the network can also be used for larger data sequences. Moreover, given that the EEG signals are significantly more dynamic and not linear, an LSTM-based approach has, by definition, an advantage given by the ability to isolate different characteristics of brain activity. In the United States, for example, this condition can be found at 48 people out of 100,000.