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Table 2 Cough flow signal extracted features.

From: Classification of voluntary cough sound and airflow patterns for detecting abnormal pulmonary function

  Time Series
1 Peak cough flow (L/s)
2 Average cough flow (L/s)
3 Maximum cough flow acceleration(L/s2)
4 Total cough volume (L)
5 Time at which 25% cough volume has been expelled/time at which 100% cough volume has been expelled
6 Time at which 50% cough volume has been expelled/time at which 100% cough volume has been expelled
7 Time at which 75% cough volume has been expelled/time at which 100% cough volume has been expelled
8 25% total time of cough/cough volume
9 50% total time of cough/cough volume
10 75% total time of cough/cough volume
11 Time at peak flow/total time
12 Crest Factor: maximum flow/Root Mean Square "RMS" flow
13 Form Factor: RMS flow/mean flow
14 Transit time: (s)
15 Skewness: where μ, and σ are the mean, and the standard deviation of the cough airflow signal respectively.
16 Kurtosis: where μ, and σ are the mean, and the standard deviation of the cough airflow signal respectively.
17 Cough flow variance
18 Cough flow variance normalized with respect to volume
19-20 The top two principal components for flow*
21-22 The top two principal components for volume*
23-24 The top two principal components for Acceleration*
  Frequency Series
25 Beta: the inverse power law 1/fβ of the power spectrum [22].
26 Wavelet parameter based on the variability in the wavelet detail coefficients found in the wavelet decomposition of the cough flow
  1. *Only the first two principal components were used, as experimentally the accuracy started to drop afterwards.