Table 1.

Feature extraction methods and features used on EEG signal dataset

Feature extraction methods	Relevant features
Time-domain features	Mean, variance, mode, median, skewness, kurtosis, max, min, zero crossing, line length, energy, power, Shannon entropy, sample entropy, approximate, entropy, fuzzy entropy, hurst exponent, standard deviation
Frequency-domain features	Spectral power, spectral entropy, energy, peak frequency, median frequency
Time–frequency-domain features	Line length, min, max, Shannon entropy, approximate entropy, standard deviation, energy, median, root mean square
Discrete Wavelet Transformation (DWT)	Bounded variation, coefficients, energy, entropy, relative bounded, variation, relative power, relative scale energy, variance, standard deviation
Continuous Wavelet Transformation (CWT)	Energy’s standard deviation, energy, coefficient z-score, entropy,
Fourier Transformation (FT)	Median frequency, power, peak frequency, spectral entropy power, spectral edge frequency, total spectral power