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  • A computer aided detection of EEG seizures in infants: a singular spectrum approach and performance comparison

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    Author(s)
    Celka, Patrick
    Griffith University Author(s)
    Celka, Patrick
    Year published
    2002
    Metadata
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    Abstract
    Presents a scalp electroencephalogram (EEG) seizure detection scheme based on singular spectrum analysis (SSA) and Rissanen minimum description length (MDL) model-order selection (SSA-MDL). Preprocessing of the signals allows for the drastic reduction of the number of false alarms. Statistical performance comparison with seizure detection schemes of Gotman et al. (1997) and Liu et al. (1992) is performed on both synthetic data and real EEG seizures. Monte Carlo simulations based on synthetic infant EEG seizure data reveals some detection drawbacks on a large variety of seizure waveforms. Detection using both Monte Carlo and ...
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    Presents a scalp electroencephalogram (EEG) seizure detection scheme based on singular spectrum analysis (SSA) and Rissanen minimum description length (MDL) model-order selection (SSA-MDL). Preprocessing of the signals allows for the drastic reduction of the number of false alarms. Statistical performance comparison with seizure detection schemes of Gotman et al. (1997) and Liu et al. (1992) is performed on both synthetic data and real EEG seizures. Monte Carlo simulations based on synthetic infant EEG seizure data reveals some detection drawbacks on a large variety of seizure waveforms. Detection using both Monte Carlo and four real infant scalp EEG signals shows the superiority of the SSA-MDL method with an average good detection rate of >93% and false detection rate <4%.
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    Journal Title
    IEEE Trans. Biomedical Eng
    Volume
    49
    DOI
    https://doi.org/10.1109/10.995684
    Copyright Statement
    © 2002 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subject
    Artificial Intelligence and Image Processing
    Biomedical Engineering
    Electrical and Electronic Engineering
    Publication URI
    http://hdl.handle.net/10072/65971
    Collection
    • Journal articles

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