Table 2 Mathematical formulas for statistical features used in the analysis.

Mean (\(\mu\))

\(\mu = \frac{1}{n} \sum _{i=1}^{n} x_i\)

The arithmetic average of all values in a segment.

Standard deviation (\(\sigma\))

\(\sigma = \sqrt{ \frac{1}{n} \sum _{i=1}^{n} (x_i - \mu )^2 }\)

The spread of data points from the mean in a segment.

Min

\(\text {min}(x_1, x_2, \dots , x_n)\)

The smallest value in the segment.

Max

\(\text {max}(x_1, x_2, \dots , x_n)\)

The largest value in the segment.

Skewness (S)

\(S = \frac{n}{(n-1)(n-2)} \sum _{i=1}^{n} \left( \frac{x_i - \mu }{\sigma }\right) ^3\)

The asymmetry of the data distribution in a segment.

Kurtosis (K)

\(K = \frac{n(n+1)}{(n-1)(n-2)(n-3)} \sum _{i=1}^{n} \left( \frac{x_i - \mu }{\sigma }\right) ^4 - \frac{3(n-1)^2}{(n-2)(n-3)}\)

The “tailedness” of the data distribution in a segment.