Research Article

A New Approach to Detect Epileptic Seizures in Electroencephalograms Using Teager Energy

Table 7

A comparison of classification accuracy achieved by our method and best performed others’ method for three classification problems.

Researcher (year)MethodDatasetClassification accuracy (%)

Tzallas et al. (2007)Time-frequency analysis and ANNZ, S100.0

Subasi and Gursoy (2010)Principal component analysis, independent component analysis, linear discriminant analysis, and support vector machinesZ, S100.0

Guo et al. (2010)Discrete wavelet transform, line length feature, and MLPNNZ, S99.6

Guo et al. (2011)Genetic programming based feature extraction and k-nearest-neighbors classifierZ, S99.0

Wang et al. (2011)Wavelet transform and Shannon entropyZ, S100.0

Iscan et al. (2011)Cross-correlation, power spectral density, support vector machines, Linear discriminant analysis and k-nearest neighbors classifierZ, S100.0

Orhan et al. (2011)Wavelet transform, k-nearest-neighbors classifier, and ANNZ, S100.0

This work (2013)Teager energy feature and ROCZ, S100.0

Ocak (2009)Discrete wavelet transform and approximate entropyZNF, S96.65

Guo et al. (2010)Discrete wavelet transform, line length feature and MLPNNZNF, S97.75

This work (2013)Teager energy feature and ROCZNF, S98.9

Tzallas et al. (2007)Time-frequency analysis and ANNZONF, S97.73

Guo et al. (2010)Discrete wavelet transform, line length feature, and MLPNNZONF, S97.77

Orhan et al. (2011)Wavelet transform, k-nearest neighbors classifier and ANNZONF, S100.0

This work (2013)Teager energy feature and ROCZONF, S97.0

This work (2013)Teager energy feature and ROCNF, S98.5