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Classification of healthy and epileptic seizure EEG signals based on different visibility graph algorithms and EEG time series

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Abstract

Recently, the idea of processing time series by transforming them onto graphs has been used in many studies. One of the simple methods proposed to convert a time series onto a graph is the visibility graph (VG). The current study investigates the ability of different VG algorithms for epileptic seizure detection. In the algorithm, single-channel Electroencephalogram (EEG) signals are transformed onto five different VG graphs, and then 13 features are generated from obtained graphs. After that, efficient features are extracted using the Sequential forward feature selection (SFFS) algorithm and classified by Random Forest (RF) into two or three classes. The experimental results show that VG algorithms are fast and easy on the performance of classification. In addition, it has shown that the proposed method not only is able to discriminate two classes with 100% accuracy, but also recognizes three classes with high accuracy, sensitivity, and specificity of 97.98%, 96.19%, and 99.12%, respectively. The comparison of this study with other methods shows the effectiveness of the proposed method for seizure detection.

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Data availability

The datasets analysed during the current study are available in the [Medizinische Einrichtungen der Universität Bonn] repository, [http://www.meb.uni-bonn.de/epileptology/science/physik/eeg.data.html].

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Authors and Affiliations

  1. Department of Electrical Engineering, Shahrood University of Technology, Shahrood, Iran

    Zeynab Mohammadpoory

  2. Department of Biomedical Engineering, Hakim Sabzevari University, Sabzevar, Iran

    Mahda Nasrolahzadeh

  3. Department of Engineering & Technology, University of Mazandaran, Babolsar, Iran

    Sekineh Asadi Amiri

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  1. Zeynab Mohammadpoory
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  2. Mahda Nasrolahzadeh
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  3. Sekineh Asadi Amiri
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Correspondence to Zeynab Mohammadpoory.

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Mohammadpoory, Z., Nasrolahzadeh, M. & Amiri, S.A. Classification of healthy and epileptic seizure EEG signals based on different visibility graph algorithms and EEG time series. Multimed Tools Appl 83, 2703–2724 (2024). https://doi.org/10.1007/s11042-023-15681-7

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