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Novel multi-view Takagi–Sugeno–Kang fuzzy system for epilepsy EEG detection

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Abstract

Most intelligent algorithms used for recognizing epilepsy electroencephalogram (EEG) have two major deficiencies. The one is the lack of interpretability and the other is unsatisfactory recognition results. In response to these challenges, we propose a dedicated model called multi-view Takagi–Sugeno–Kang (TSK) fuzzy system (MV-TSK-FS) for the epilepsy EEG detection. Our contributions lie in three aspects. First, TSK-FS is selected as the basic model. As one of the most famous fuzzy systems, TSK-FS has the advantage of nice interpretability and thus meets the requirement of clinic trials and applications. Second, MV-TSK-FS uses a multi-view framework to collaboratively handle the collective feature data extracted from diverse extraction perspectives, which strives to avoid the potential performance degradation commonly incurred with single feature extraction. Third, we propose a view-weighted mechanism based on the quadratic regularization to distinguish the importance of each view. The more important the view, the larger the corresponding weight is. The final decision is consequently figured out with the weighted outputs of all views. Experimental results demonstrate that, compared with other epilepsy EEG detection ones, our proposed method has better classification performance as well as more satisfied interpretability on results.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grants 61702225, 61772241, and U20A20228, by the 2018 Six Talent Peaks Project of Jiangsu Province under Grant XYDXX-127, by a Science and Technology Demonstration Project for the Social Development of Wuxi under Grant WX18IVJN002, and by the Jiangsu Committee of Health under Grant H2018071.

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Authors and Affiliations

  1. School of Artificial Intelligence and Computer Science, Jiangnan University, 1800 Lihu Avenue, Wuxi, 214122, Jiangsu, People’s Republic of China

    Yarong Li, Pengjiang Qian & Shitong Wang

  2. Department of Cardiovascular Science, University of Leicester, University Road, Leicester, LE1 7RH, UK

    Shuihua Wang

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  1. Yarong Li
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  2. Pengjiang Qian
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  3. Shuihua Wang
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  4. Shitong Wang
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Correspondence to Pengjiang Qian.

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Li, Y., Qian, P., Wang, S. et al. Novel multi-view Takagi–Sugeno–Kang fuzzy system for epilepsy EEG detection. J Ambient Intell Human Comput 14, 5625–5645 (2023). https://doi.org/10.1007/s12652-021-03189-7

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