Table 1.

Description of the features set. The dataset was composed of 26 numerical-continuous parameters

ID	Parameter	Description
1	Mean frequency	It summarizes the spectra by defining the spectral centroid
2	Median frequency	Frequency that divides the power spectrum into two parts of equal area
3	Spectral crest factor (SCF)	SCF quantifies the tonality of the signal by providing an estimation of its irregularity in terms of ‘flatness’. High values suggest the presence of a dominant spectral component
4	Shannon entropy
5	Rényi entropy	Quantifies irregularity in time frequency distributions
6	Tsallis entropy
7	RP in the 50–200 Hz band	The frequency band (50–200 Hz) is related to vesicular sounds
8	RP in the 200–400 Hz band	Low-frequency wheezes, rhonchi and coarse crackles are located in this band
9	RP in the 400–800 Hz band	This band contains fine crackles and high-frequency wheezes
10	RP in the 800–2000 Hz band	High-frequency noise mainly originated by airflow turbulences in the trachea
11	Second-order moment	Second-order spectral moment. Variance of the power spectrum
12	Skewness	Third-order spectral moment. Degree of asymmetry
13	Kurtosis	Fourth-order spectral moment. Measure of whether the data are peaked or flat relative to a normal distribution

These indexes identified spectral characteristics and were calculated from short-time Fourier transform analysis applied to the respiratory sound signals.

RP, relative power referred to (0, 2000 Hz).