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Future Access Enablers for Ubiquitous and Intelligent Infrastructures. 4th EAI International Conference, FABULOUS 2019, Sofia, Bulgaria, March 28-29, 2019, Proceedings

Research Article

EEG Signal Processing: Applying Deep Learning Methods to Identify and Classify Epilepsy Episodes

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  • @INPROCEEDINGS{10.1007/978-3-030-23976-3_6,
        author={George Suciu and Maria-Cristina Dițu},
        title={EEG Signal Processing: Applying Deep Learning Methods to Identify and Classify Epilepsy Episodes},
        proceedings={Future Access Enablers for Ubiquitous and Intelligent Infrastructures. 4th EAI International Conference, FABULOUS 2019, Sofia, Bulgaria, March 28-29, 2019, Proceedings},
        proceedings_a={FABULOUS},
        year={2019},
        month={9},
        keywords={Epilepsy EEG Strokes},
        doi={10.1007/978-3-030-23976-3_6}
    }
    
  • George Suciu
    Maria-Cristina Dițu
    Year: 2019
    EEG Signal Processing: Applying Deep Learning Methods to Identify and Classify Epilepsy Episodes
    FABULOUS
    Springer
    DOI: 10.1007/978-3-030-23976-3_6
George Suciu1,*, Maria-Cristina Dițu,*
  • 1: Beia Consult International
*Contact email: george@beia.ro, maria.ditu@beia.ro

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.

Keywords
Epilepsy EEG Strokes
Published
2019-09-17
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-23976-3_6
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