Table 1.

List of features, descriptions, and formula.

	Feature	Description	Formula
F1	Zero crossing (ZC)	The number of times the demeaned data change sign.	${\Sigma }_{i=2}^N\mathrm{\text{sgn}}(-x_{i-1}{x}_i)$
F2	Slope sign changes (SSC)	The number of times the differential data change sign.	${\Sigma }_{i=3}^N\mathrm{\text{sgn}}\left[-(x_i-x_{i-1})(x_{i-1}-x_{i-2})\right]$
F3	Waveform length (WL)	The summation of the absolute values of the differential data.	${\Sigma }_{i=2}^N|x_i-x_{i-1}|$
F4	Wilson amplitude (WA)	The number of times the change in the signal amplitudes of two consecutive samples exceeds the standard deviation.	${\Sigma }_{i=2}^N\mathrm{\text{sgn}}(|x_i-x_{i-1}|-x_{std})$
F5	Mean absolute (MAB)	The average of the absolute values of the data.	$\frac{1}{N}{\Sigma }_{i=1}^N\left|x_i\right|$
F6	Mean square (MSQ)	The average of the square values of the data.	$\frac{1}{N}{\Sigma }_{i=1}^N{x}_i^2$
F7	Root mean square (RMS)	The root of MSQ or v-order 2.	$\sqrt{\frac{1}{N}{\Sigma }_{i=1}^N{x}_i^2}$
F8	V-order 3 (V3)	The cubic root of the average of the cube of the data.	$\sqrt[3]{\frac{1}{N}{\Sigma }_{i=1}^N{x}_i^3}$
F9	Log detector (LD)	The exponential of the average of the log data.	$\mathrm{\text{exp}}(\frac{1}{N}{\Sigma }_{i=1}^N\mathrm{\text{log}}\left|x_i\right|)$
F10	Difference absolute standard deviation (DABS)	Standard deviation of the absolute of the differential data.	$\sqrt{\frac{1}{N-1}{\Sigma }_{i=2}^N{(x_i-x_{i-1})}^2}$
F11	Maximum fractal length (MFL)	Equivalent to the log of DABS minus an offset that is equal to 1/2log(N−1)	$\mathrm{\text{log}}\left[\sqrt{{\Sigma }_{i=2}^N{(x_i-x_{i-1})}^2}\right]$
F12	Myopulse percentage rate (MPR)	The number of times the absolute of the data exceeds the standard deviation.	${\Sigma }_{i=1}^N\mathrm{\text{sgn}}(\left|x_i\right|-x_{std})$
F13	Mean absolute value slope (MAVS)	A modified version of MAV that is the difference between the MAV of the first half of a signal window and the second half.	$\frac{{\Sigma }_{i=1}^{\lfloor N/2\rfloor }\left|x_i\right|-{\Sigma }_{i=\lfloor N/2\rfloor + 1}^N\left|x_i\right|}{\lfloor N/2\rfloor }$
F14	Weighted mean absolute (WMA)	A modified version of the MAB where the first and last 25% of a signal window is given less weight than the middle 50%.	$\frac{1}{N}{\Sigma }_{i=1}^N{w}_i\left|x_i\right|$ where wi = 1 if i∈[0.25N, 0.75N], and wi = 0.5 otherwise