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research-article

Epileptic Seizure Prediction by Synthesizing EEG Signals through GPT

Authors:

Mei ZhangAuthors Info & Claims

AIPR '21: Proceedings of the 2021 4th International Conference on Artificial Intelligence and Pattern Recognition

Pages 419 - 423

https://doi.org/10.1145/3488933.3489016

Published: 25 February 2022 Publication History

Abstract

Epileptic seizures have a serious impact on the normal life of patients with epilepsy. Epileptic seizure prediction can effectively reduce the mental pressure of patients with epilepsy and improve patients' quality of life. It is a key and challenging task to predict seizures from Electroencephalogram (EEG) data collected by EEG acquisition devices. To improve the accuracy of epileptic prediction, this paper proposes a method of epileptic seizure prediction based on synthetic EEG signals by Generative Pre-Training (GPT). The EEG data generated by this method is added into the actual EEG data, which effectively improves the accuracy of epilepsy prediction. In the experiments on MIT Public scalp EEG data set, through GPT EEG data enhancement, the average prediction accuracy of 10 minutes before seizure increased from 95.26% to 97.15%. The experimental results show that the proposed method is effective.

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Cited By

Grubov VNazarikov SKurkin SUtyashev NAndrikov DKarpov OHramov A(2024)Two-Stage Approach With Combination of Outlier Detection Method and Deep Learning Enhances Automatic Epileptic Seizure DetectionIEEE Access10.1109/ACCESS.2024.345303912(122168-122182)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3453039
Carrle FHollenbenders YReichenbach A(2023)Generation of synthetic EEG data for training algorithms supporting the diagnosis of major depressive disorderFrontiers in Neuroscience10.3389/fnins.2023.121913317Online publication date: 2-Oct-2023
https://doi.org/10.3389/fnins.2023.1219133
Zilelioglu HKhodabandelou GChibani AAmirat Y(2023)Conditional Human Activity Signal Generation and Generative Classification with a GPT-2 Model2023 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN54540.2023.10191464(1-8)Online publication date: 18-Jun-2023
https://doi.org/10.1109/IJCNN54540.2023.10191464

Index Terms

Epileptic Seizure Prediction by Synthesizing EEG Signals through GPT
1. Applied computing
  1. Life and medical sciences
2. Computing methodologies
  1. Machine learning

Index terms have been assigned to the content through auto-classification.

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AIPR '21: Proceedings of the 2021 4th International Conference on Artificial Intelligence and Pattern Recognition

September 2021

715 pages

ISBN:9781450384087

DOI:10.1145/3488933

Copyright © 2021 ACM.

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Publication History

Published: 25 February 2022

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AIPR 2021: 2021 4th International Conference on Artificial Intelligence and Pattern Recognition

September 24 - 26, 2021

Xiamen, China

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Cited By

Grubov VNazarikov SKurkin SUtyashev NAndrikov DKarpov OHramov A(2024)Two-Stage Approach With Combination of Outlier Detection Method and Deep Learning Enhances Automatic Epileptic Seizure DetectionIEEE Access10.1109/ACCESS.2024.345303912(122168-122182)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3453039
Carrle FHollenbenders YReichenbach A(2023)Generation of synthetic EEG data for training algorithms supporting the diagnosis of major depressive disorderFrontiers in Neuroscience10.3389/fnins.2023.121913317Online publication date: 2-Oct-2023
https://doi.org/10.3389/fnins.2023.1219133
Zilelioglu HKhodabandelou GChibani AAmirat Y(2023)Conditional Human Activity Signal Generation and Generative Classification with a GPT-2 Model2023 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN54540.2023.10191464(1-8)Online publication date: 18-Jun-2023
https://doi.org/10.1109/IJCNN54540.2023.10191464

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