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A signal regularity-based automated seizure prediction algorithm using long-term scalp EEG recordings

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Cybernetics and Systems Analysis Aims and scope

Abstract

The purpose of this study was to evaluate a signal regularity-based automated seizure prediction algorithm for scalp EEG. Signal regularity was quantified using the Pattern Match Regularity Statistic (PMRS), a statistical measure. The primary feature of the prediction algorithm is the degree of convergence in PMRS (“PMRS entrainment”) among the electrode groups determined in the algorithm training process. The hypothesis is that the PMRS entrainment increases during the transition between interictal and ictal states, and therefore may serve as an indicator for prediction of an impending seizure.

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Author information

Authors and Affiliations

  1. Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA

    Jui-Hong Chien & P. M. Pardalos

  2. Optima Neuroscience, Inc., Gainesville, USA

    Jui-Hong Chien, Deng-Shan Shiau, R. T. Kern & J. Ch. Sackellares

  3. Scientific Affairs, Gainesville, FL, USA

    Deng-Shan Shiau

  4. Medical University of South Carolina, Charleston, SC, USA

    J. J. Halford

  5. Drexel University College of Medicine, Philadelphia, PA, USA

    K. M. Kelly

  6. Allegheny General Hospital and Allegheny-Singer Research Institute, Pittsburgh, PA, USA

    K. M. Kelly

  7. Department of Statistics, University of Florida, Gainesville, FL, USA

    M. C. K. Yang

  8. Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA

    Jicong Zhang & P. M. Pardalos

  9. Department of Computer & Information Science & Engineering, University of Florida, Gainesville, FL, USA

    P. M. Pardalos

Authors
  1. Jui-Hong Chien
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  9. P. M. Pardalos
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Corresponding author

Correspondence to Jui-Hong Chien.

Additional information

This work was supported by the grants 5R01NS050582 (JCS) and 1R43NS064647 (DSS) from NIH-NINDS.

Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 95–107, July–August 2011.

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Chien, JH., Shiau, DS., Halford, J.J. et al. A signal regularity-based automated seizure prediction algorithm using long-term scalp EEG recordings. Cybern Syst Anal 47, 586–597 (2011). https://doi.org/10.1007/s10559-011-9339-x

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  • DOI: https://doi.org/10.1007/s10559-011-9339-x

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