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Dynamical graph neural network with attention mechanism for epilepsy detection using single channel EEG

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Abstract

Epilepsy is a chronic brain disease, and identifying seizures based on electroencephalogram (EEG) signals would be conducive to implement interventions to help patients reduce impairment and improve quality of life. In this paper, we propose a classification algorithm to apply dynamical graph neural network with attention mechanism to single channel EEG signals. Empirical mode decomposition (EMD) are adopted to construct graphs and the optimal adjacency matrix is obtained by model optimization. A multilayer dynamic graph neural network with attention mechanism is proposed to learn more discriminative graph features. The MLP-pooling structure is proposed to fuse graph features. We performed 12 classification tasks on the epileptic EEG database of the University of Bonn, and experimental results showed that using 25 runs of ten-fold cross-validation produced the best classification results with an average of 99.83\(\%\) accuracy, 99.91\(\%\) specificity, 99.78\(\%\) sensitivity, 99.87\(\%\) precision, and 99.47\(\%\) \(F_1\) score for the 12 classification tasks.

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Funding

This study was supported by Shandong Provincial Natural Science Foundation of China (ZR2019ZD01, ZR2020MF143, and ZR2020MF027)

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Authors and Affiliations

  1. School of Information Science and Engineering, Shandong University, Qingdao, 266237, China

    Yang Li, Yang Yang, Qinghe Zheng, Hongjun Wang & Penghui Zhao

  2. Center for Optics Research and Engineering, Shandong University, Qingdao, 266237, China

    Yunxia Liu

  3. Public (Innovation) Experimental Teaching Center, Shandong University, Qingdao, 266237, China

    Hongjun Wang

  4. The second hospital of Shandong University, Jinan, 250033, China

    Shangling Song

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  1. Yang Li
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  2. Yang Yang
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  6. Shangling Song
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  7. Penghui Zhao
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Correspondence to Yang Yang or Hongjun Wang.

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Li, Y., Yang, Y., Zheng, Q. et al. Dynamical graph neural network with attention mechanism for epilepsy detection using single channel EEG. Med Biol Eng Comput 62, 307–326 (2024). https://doi.org/10.1007/s11517-023-02914-y

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