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International Conference on Machine Learning and Intelligent Communications

MLICOM 2020: Machine Learning and Intelligent Communications pp 129–136Cite as

Seizure Detection Using Deep Discriminative Multi-set Canonical Correlation Analysis

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Abstract

Due to the nonlinear and nonstationary properties in EEG signals, some seizure detection methods tried to decompose EEG signal into nonlinear and nonstationary components and use them for feature extraction. Seizure detection results showed a certain degree of improvement in these approaches. Based on this idea, more signal decomposition methods have been explored. Signal decomposition methods are designed according to different principles, which show different properties of signals. So, it can be more effective using features extracted from different signal decomposition methods. Based on this consideration, a novel method for seizure detection based on feature combination exploiting deep neural network is proposed in this paper. We introduced a discriminative extension of Deep Multi-set Canonical Correlation Analysis (DMCCA) for seizure detection. Features extracted from different decomposed signals are combined by a joint optimization target of discriminative loss and multi-set canonical correlation loss, which is both discriminative and canonical correlated. Preliminary experiments show the proposed method improves seizure detection results in terms of accuracy and AUC.

This research is supported by Young Innovative Talents Project of 2018 Guangdong University’s key scientific research platform and scientific research project, project number: 2018GkQNCX087.

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Authors and Affiliations

  1. School of Computer, Shenzhen Institute of Information Technology, Shenzhen, China

    Xuefeng Bai, Lijun Yan & Yang Li

Authors
  1. Xuefeng Bai
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  2. Lijun Yan
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  3. Yang Li
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Correspondence to Xuefeng Bai .

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Editors and Affiliations

  1. Shenzhen Institute of Information Technology, Shenzhen, China

    Mingxiang Guan

  2. Sci & Tech, DianHang Bldg, Rm 321, Dalian Maritime Univ, Sch of Info, Dalian, Liaoning, China

    Zhenyu Na

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Bai, X., Yan, L., Li, Y. (2021). Seizure Detection Using Deep Discriminative Multi-set Canonical Correlation Analysis. In: Guan, M., Na, Z. (eds) Machine Learning and Intelligent Communications. MLICOM 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 342. Springer, Cham. https://doi.org/10.1007/978-3-030-66785-6_15

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  • DOI: https://doi.org/10.1007/978-3-030-66785-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-66784-9

  • Online ISBN: 978-3-030-66785-6

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