A real-time epilepsy seizure detection approach based on EEG using short-time Fourier transform and Google-Net convolutional neural network
Article
Article Title | A real-time epilepsy seizure detection approach based on EEG using short-time Fourier transform and Google-Net convolutional neural network |
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ERA Journal ID | 212685 |
Article Category | Article |
Authors | Shen, Mingkan, Yang, Fuwen, Wen, Peng, Song, Bo and Li, Yan |
Journal Title | Heliyon |
Journal Citation | 10 (11) |
Article Number | e31827 |
Number of Pages | 12 |
Year | 2024 |
Publisher | Elsevier |
Place of Publication | United Kingdom |
ISSN | 2405-8440 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.heliyon.2024.e31827 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S2405844024078587 |
Abstract | Epilepsy is one of the most common brain disorders, and seizures of epilepsy have severe adverse effects on patients. Real-time epilepsy seizure detection using electroencephalography (EEG) signals is an important research area aimed at improving the diagnosis and treatment of epilepsy. This paper proposed a real-time approach based on EEG signal for detecting epilepsy seizures using the STFT and Google-net convolutional neural network (CNN). The CHB-MIT database was used to evaluate the performance, and received the results of 97.74 % in accuracy, 98.90 % in sensitivity, 1.94 % in false positive rate. Additionally, the proposed method was implemented in a real-time manner using the sliding window technique. The processing time of the proposed method just 0.02 s for every 2-s EEG episode and achieved average 9.85- second delay in each seizure onset. |
Keywords | Epilepsy seizure detection ; EEG; Real-time ; STFT; Google-net CNN |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 461104. Neural networks |
400607. Signal processing | |
400399. Biomedical engineering not elsewhere classified | |
Byline Affiliations | School of Engineering |
Griffith University | |
School of Mathematics, Physics and Computing |
https://research.usq.edu.au/item/z9911/a-real-time-epilepsy-seizure-detection-approach-based-on-eeg-using-short-time-fourier-transform-and-google-net-convolutional-neural-network
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