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Efficient Frameworks for EEG Epileptic Seizure Detection and Prediction

Author

Listed:
  • Heba M. Emara

    (Menoufia University)

  • Mohamed Elwekeil

    (Menoufia University)

  • Taha E. Taha

    (Menoufia University)

  • Adel S. El-Fishawy

    (Menoufia University)

  • El-Sayed M. El-Rabaie

    (Menoufia University)

  • Walid El-Shafai

    (Menoufia University
    Prince Sultan University)

  • Ghada M. El Banby

    (Menoufia University)

  • Turky Alotaiby

    (KACST)

  • Saleh A. Alshebeili

    (King Saud University
    King Saud University)

  • Fathi E. Abd El-Samie

    (Menoufia University
    Princess Nourah Bint Abdulrahman University)

Abstract

Seizure detection and prediction are a very hot topics in medical signal processing due to their importance in automatic medical diagnosis. This paper presents three efficient frameworks for applications related to electroencephalogram (EEG) signal processing. The first one is an automatic seizure detection framework based on the utilization of scale-invariant feature transform (SIFT) as an extraction tool. The second one depends on the utilization of the fast Fourier transform (FFT) and an artificial neural network for epileptic seizure prediction. Finally, an automated patient-specific framework for channel selection and seizure prediction is presented based on FFT. The simulation results show the success of the proposed frameworks for automated medical diagnosis.

Suggested Citation

  • Heba M. Emara & Mohamed Elwekeil & Taha E. Taha & Adel S. El-Fishawy & El-Sayed M. El-Rabaie & Walid El-Shafai & Ghada M. El Banby & Turky Alotaiby & Saleh A. Alshebeili & Fathi E. Abd El-Samie, 2022. "Efficient Frameworks for EEG Epileptic Seizure Detection and Prediction," Annals of Data Science, Springer, vol. 9(2), pages 393-428, April.
  • Handle: RePEc:spr:aodasc:v:9:y:2022:i:2:d:10.1007_s40745-020-00308-7
    DOI: 10.1007/s40745-020-00308-7
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    References listed on IDEAS

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    1. Rabia Aziz & C. K. Verma & Namita Srivastava, 2018. "Artificial Neural Network Classification of High Dimensional Data with Novel Optimization Approach of Dimension Reduction," Annals of Data Science, Springer, vol. 5(4), pages 615-635, December.
    2. Mohiuddin Ahmed & A. K. M. Najmul Islam, 2020. "Deep Learning: Hope or Hype," Annals of Data Science, Springer, vol. 7(3), pages 427-432, September.
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