Seizure Onset Detection based on a Uni- or Multi-modal Intelligent Seizure Acquisition (UISA/MISA) System

Isa Conradsen, Sándor Beniczky, Peter Wolf, Jonas Duun-Henriksen, Thomas Sams, Helge Bjarup Dissing Sørensen

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    Abstract

    An automatic Uni- or Multi-modal Inteligent Seizure Acquisition (UISA/MISA) system is highly applicable for onset detection of epileptic seizures based on motion data. The modalities used are surface electromyography (sEMG), acceleration (ACC) and angular velocity (ANG). The new proposed automatic algorithm on motion data is extracting features as “log-sum” measures of discrete wavelet components. Classification into the two groups “seizure” versus “nonseizure” is made based on the support vector machine (SVM) algorithm. The algorithm performs with a sensitivity of 91-100%, a median latency of 1 second and a specificity of 100% on multi-modal data from five healthy subjects simulating seizures. The uni-modal algorithm based on sEMG data from the subjects and patients performs satisfactorily in some cases. As expected, our results clearly show superiority of the multimodal approach, as compared with the uni-modal one.
    Original languageEnglish
    Title of host publication2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
    PublisherIEEE
    Publication date2010
    Pages3269-3272
    ISBN (Print)978-1-4244-4123-5
    DOIs
    Publication statusPublished - 2010
    Event32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Buenos Aires, Argentina
    Duration: 31 Aug 20104 Sept 2010
    Conference number: 32
    http://embc2010.embs.org/

    Conference

    Conference32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
    Number32
    Country/TerritoryArgentina
    CityBuenos Aires
    Period31/08/201004/09/2010
    Internet address
    SeriesI E E E Engineering in Medicine and Biology Society. Conference Proceedings
    ISSN2375-7477

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