Real-time epilepsy seizure detection based on EEG using tunable-Q wavelet transform and convolutional neural network
Article
Article Title | Real-time epilepsy seizure detection based on EEG using tunable-Q wavelet transform and convolutional neural network |
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ERA Journal ID | 3391 |
Article Category | Article |
Authors | Shen, Mingkan, Wen, Peng, Song, Bo and Li, Yan |
Journal Title | Biomedical Signal Processing and Control |
Journal Citation | 82 |
Article Number | 104566 |
Number of Pages | 9 |
Year | 2023 |
Publisher | Elsevier |
Place of Publication | Netherlands |
ISSN | 1746-8094 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.bspc.2022.104566 |
Web Address (URL) | https://www.sciencedirect.com/science/article/abs/pii/S1746809422010205 |
Abstract | Epilepsy is a chronic disease caused by sudden abnormal discharge of brain neurons, leading to transient brain dysfunctions. This paper proposed an EEG based real-time approach to detect epilepsy seizures using tunable-Q wavelet transform and convolutional neural network (CNN). Statistical moments and spectral band power were used to reveal the time domain and frequency domain features in EEG, and then were converted into imaged-like data fed into CNN. The proposed approach was evaluated using the database CHB-MIT. The proposed algorithm achieved 97.57% in accuracy, 98.90% in sensitivity, 2.13% in false positive rate and 10.46-second delay. In addition, the proposed method is suitable in real-time implementation. The outcomes indicate that the proposed method can applied to real-time seizure detection in clinical applications. |
Keywords | CNN; EEG; Real-time; Seizure detection; Tunable-Q wavelet transform |
Related Output | |
Is part of | Real-time epilepsy seizure detection and brain connectivity analysis using electroencephalogram |
ANZSRC Field of Research 2020 | 400309. Neural engineering |
461104. Neural networks | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
This article is part of a UniSQ Thesis by publication. See Related Output. | |
Byline Affiliations | University of Southern Queensland |
School of Engineering | |
School of Mathematics, Physics and Computing |
https://research.usq.edu.au/item/w5xvq/real-time-epilepsy-seizure-detection-based-on-eeg-using-tunable-q-wavelet-transform-and-convolutional-neural-network
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