Table 3 Accuracy of some relevant studies which have used the Bonn EEG dataset. Five classification problems were mentioned for comparison
From: Applying nonlinear measures to the brain rhythms: an effective method for epilepsy diagnosis
Authors | Method | Classifier | Accuracy (%) |
|---|---|---|---|
AB/CD/E | |||
Orhan et al.[41] | Wavelet (DWT) and probability distributions by K-means clustering | ANN | 95.60 |
Acharya et al.[42] | Entropy Measures | Fuzzy Classifier | 98.1 |
Murugavel and Ramakrishnan[43] | Wavelet + LLE + ApEn | Hierarchical SVM | 95 |
This work | Nonlinear features | MLPNN | 98.19 |
A/D/E | |||
Acharya et al. [44] | Recurrence quantification analysis | SVM | 95.6 |
Orhan et al. [41] | Wavelet (DWT) and probability distributions by K-means clustering | ANN | 96.67 |
Wang et al. [45] | Multi-scale blanket dimension and fractal intercepts | SVM | 97.13 |
Murugavel and Ramakrishnan [43] | Wavelet + LLE + ApEn | Hierarchical SVM | 96 |
This work | Nonlinear features | MLPNN | 98.5 |
ABCD/E | |||
Guo et al. [46] | Wavelet (DWT) + line length | ANN | 97.7 |
Murugavel and Ramakrishnan [43] | Wavelet + LLE + ApEn | Hierarchical SVM | 99 |
Orhan et al. [41] | Wavelet (DWT) and probability distributions by K-means clustering | ANN | 99.60 |
Kumar et al. [47] | Wavelet(DWT) and Approximate Entropy | ANN, SVM | 94 |
This work | Nonlinear features | MLPNN | 99.91 |
A/E | |||
Guo et al. [46] | Wavelet (DWT) + line length | ANN | 99.6 |
Orhan et al. [41] | Wavelet (DWT) and probability distributions by K-means clustering | ANN | 100 |
Nicolaou et al. [48] | Permutation Entropy | SVM | 93.55 |
Kumar et al. [47] | Wavelet(DWT) and Approximate Entropy | ANN, SVM | 100 |
Wang et al. [45] | Multi-scale blanket dimension and fractal intercepts | SVM | 99.83 |
Kaya et al. [49] | 1D- local binary pattern | BayesNet, Functional Tree | 99.50 |
Murugavel and Ramakrishnan [43] | Wavelet + LLE + ApEn | Hierarchical SVM | 99 |
This work | Nonlinear features | MLPNN | 100 |
D/E | |||
Kumar et al. [47] | Wavelet(DWT) and Approximate Entropy | ANN, SVM | 95 |
Nicolaou et al. [48] | Permutation Entropy | SVM | 83.13 |
Kaya et al. [49] | 1D-local binary pattern | BayesNet, Functional Tree | 95.50 |
This work | Nonlinear features | MLPNN | 99.84 |