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            Epileptic Seizures and the EEG

            Measurement, Models, Detection and Prediction

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            Author(s)
            Varsavsky, Andrea
            Mareels, Iven
            Cook, Mark
            Language
            English
            Show full item record
            Abstract
            A study of epilepsy from an engineering perspective, this volume begins by summarizing the physiology and the fundamental ideas behind the measurement, analysis and modeling of the epileptic brain. It introduces the EEG and provides an explanation of the type of brain activity likely to register in EEG measurements, offering an overview of how these EEG records are and have been analyzed in the past. The book focuses on the problem of seizure detection and surveys the physiologically based dynamic models of brain activity. Finally, it addresses the fundamental question: can seizures be predicted? Based on the authors' extensive research, the book concludes by exploring a range of future possibilities in seizure prediction.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/184028
            Keywords
            Neuroscience; Biomedical Engineering; NEUROSCIENCE; BIOSCIENCE; SCI-TECH; BIOMEDICALSCIENCE; STM; action; column; conduction; cortical; epilepsies; focal; potential; record; scalp; volume; thema EDItEUR::M Medicine and Nursing::MF Pre-clinical medicine: basic sciences; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences; thema EDItEUR::M Medicine and Nursing::MQ Nursing and ancillary services::MQW Biomedical engineering
            DOI
            10.1201/b10459
            Publisher
            Taylor & Francis
            Publisher website
            http://www.taylorandfrancis.com/
            Publication date and place
            2011
            Imprint
            CRC Press
            Pages
            370
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            Credits


            • logo Investir l'avenirInvestir l'avenir
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            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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