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Table 5 Comparison results of some epileptic seizure detection methods

From: Automated epileptic seizures detection using multi-features and multilayer perceptron neural network

Author Features Classifier Results Database
Kiymik et al. Autoregressive features Back-propagation neural network Accuracy 95% Neurology department of the Medical Faculty Hospital of Dicle University
Orhan et al. DWT-based features MLPNN Accuracy 99.6 University of Bonn
Kamath 2013 Teager energy Radial basis function neural network Accuracy 97.8% University of Bonn
Gurwinder et al. 2015 Wavelet transformation and spike-based features MLPNN Accuracy 98.6 University of Bonn
Ahammad et al. Energy, entropy, standard deviation, maximum, minimum, and mean MLPNN Accuracy 84.2 University of Bonn
Wang et al. 2011 Wavelet packet entropy K-NN Accuracy 100% University of Bonn
Abbasi et al. 2017 DWT-based features MLPNN 98.33% University of Bonn
Srinivasan et al. 2007 ApEn Recurrent Elman neural network Accuracy 100% University of Bonn
Proposed method PSD, entropy, and Teager energy MLPNN Sensitivity 97.8%
Specificity 96.4%
FDR 1 h−1
Ramaiah Memorial College and Hospital, Bengaluru