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Table 8 A comparison of performances of the various methods for detection of epileptic seizures applied to the dataset from [21, 22] (reproduced from [26, 34]).

From: Combination of EEG Complexity and Spectral Analysis for Epilepsy Diagnosis and Seizure Detection

Classes Authors (year) Method Dataset Accuracy
2 Nigam et al. [23] (2004) Nonlinear preprocessing filter, diagnostic artificial neural network (LAMSTAR) A, E 97.2
  Srinivasan et al. [14] (2005) Time & frequency domain features, recurrent neural network (RNN) A, E 99.6
  Kannathal et al. [8] (2005) Entropy measures, adaptive neurofuzzy inference system (ANFIS) A, E 92.22
  Polat et al. [24] (2006) Fast Fourier transform (FFT), decisiontree (DT) A, E 98.72
  Subasi [25] (2007) Discrete wavelet transform (DWT), mixture of expert model A, E 95
  Srinivasan et al. [12] (2007) Approximate entropy, artificial neural network A, E 100
  Tzallas et al. [26] (2007) Time frequency (TF) analysis, artificial neural network (ANN) (A, B, C, D), E 97.73
  Ocak [27] (2008) Approximate entropy & discrete wavelet transform (DWT), genetic algorithm(GA) (A, B, C, D), E 96.15
  This paper Time frequency & approximate entropy analysis, linear or nonlinear classifiers (A, B, C, D), E 97.82–98.51
3 Guler et al. [28] (2005) Lyapunov exponents, recurrent neural network (RNN) A, D, E 96.79
  Sadati et al. [29] (2006) Discrete wavelet transform (DWT), adaptive neural fuzzy network (ANFN) A, D, E 85.9
  Ghosh-Dastidat et al. [18] (2008) Chaos theory and wavelet analysis, PCA, radical basis function neural network A, D, E 96.73
  Mousavi et al. [30] (2008) AR model, wavelet decomposition, MLP classifier A, C, E 96
  This paper Time frequency & approximate entropy analysis, linear or nonlinear classifiers A, D, E 96.83–98.67
5 Güler et al. [32] (2005) Wavelet transform, adaptive neurofuzzy inference system A, B, C, D, E 98.68
  Güler et al. [33] (2007) Wavelet transform, Lyapunov exponents, support vector machine A, B, C, D, E 99.28
  Übeyli et al. [31] (2007) Eigenvector methods, Mixture of expert models A, B, C, D, E 98.60
  Tzallas et al. [34] (2009) Time frequency (TF) analysis, artificial neural network (ANN) A, B, C, D, E 89
  This paper Time frequency & approximate entropy analysis, RBFSVM A, B, C, D, E 85.9