... Frequency domain: power spectral density, band power >> using Fourier Transform 29 [26,49,63,74,104,105,107,116,123,149,161,169,176,193,197,200,203,204,207,208,216,[218][219][220][221][222][223][224][225] Time domain: Activity, mobility and complexity >> using Hjorth Parameters, Fractal dimension >> using Higuchi Method 11 [107,117,200,203,204,206,213,216,220,222,224] Wavelet domain: Entropy, Energy >> using Wavelet Transform 7 [186,201,203,213,216,217,226] Statistical features: Median, Standard deviation, Kurtosis symmetry, etc. 6 [6,104,117,200,204,226] Classification Support Vector Machine (SVM) 24 [49,104,106,107,116,117,157,176,186,190,193,196,197,[202][203][204]213,216,218,220,[225][226][227][228] K-Nearest Neighbor (k-NN) 10 [49,104,107,190,204,207,213,216,218,228] Linear Discriminant Analysis (LDA) 4 [26,123,176,227] Artificial Neural Network (ANN) 7 [105,176,190,204,216,223,227] It is noteworthy to mention that a single feature extraction technique is not optimal across all of the applications. Besides, existing signals are not enough for high accuracy feature extraction. ...