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62744

Efficient Epileptic Seizure Prediction Approach Based on Hilbert Transform

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Last updated: 25 Dec 2024

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Abstract

This paper introduces a patient-specific method for seizure prediction applied to scalp Electroencephalography (sEEG) signals. The proposed method depends on computing the instantaneous amplitude of the analytic signal by applying Hilbert transform on EEG signals. Then, the Probability Density Functions (PDFs) are estimated for amplitude, local mean, local variance, derivative and median as major features. This is followed by a threshold-based classifier which discriminates between pre-ictal and inter-ictal periods. The proposed approach utilizes an adaptive algorithm for channel selection to identify the optimum number of needed channels which is useful for real-time applications. It is applied to all patients from the CHB-MIT database, achieving an average prediction rate of 96.46%, an average false alarm rate of 0.028077/h and an average prediction time of 60.1595 minutes using a 90-minute prediction horizon. Experimental results prove that Hilbert transform is more efficient for prediction than other existing approaches.

DOI

10.21608/mjeer.2019.62744

Authors

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Heba

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Emara

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Affiliation

Faculty of Electronic Engineering, Menoufia University, Menouf , Egypt

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First Name

Mohamed

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Elwekeil

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Faculty of Electronic Engineering, Menoufia University, Menouf , Egypt

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First Name

taha

Last Name

Taha

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E.

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Faculty of Electronic Engineering, Menoufia University, Menouf , Egypt

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First Name

Adel

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El-Fishawy

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Faculty of Electronic Engineering, Menoufia University, Menouf , Egypt

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First Name

Sayed

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El-Rabaie

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-

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Faculty of Electronic Engineering, Menoufia University, Menouf , Egypt

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First Name

Turky

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Alotaiby

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Affiliation

KACST, Kingdom of Saudi Arabia

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First Name

Saleh

Last Name

Alshebeili

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-

Affiliation

Electrical Engineering Department, KACST-TIC in Radio Frequency and Photonics for the e-Society (RFTONICS), King Saud University.

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First Name

Fathi

Last Name

Abd el-samie

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Faculty of Electronic Engineering, Menoufia University, Menouf , Egypt.

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Volume

28

Article Issue

2

Related Issue

9507

Issue Date

2019-07-01

Receive Date

2018-05-24

Publish Date

2019-07-01

Page Start

17

Page End

32

Print ISSN

1687-1189

Online ISSN

2682-3535

Link

https://mjeer.journals.ekb.eg/article_62744.html

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https://mjeer.journals.ekb.eg/service?article_code=62744

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Original Article

Type Code

1,088

Publication Type

Journal

Publication Title

Menoufia Journal of Electronic Engineering Research

Publication Link

https://mjeer.journals.ekb.eg/

MainTitle

Efficient Epileptic Seizure Prediction Approach Based on Hilbert Transform

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Article

Created At

22 Jan 2023