Table 2 Cough flow signal extracted features.
| Â | 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: |
15 | Skewness: |
16 | Kurtosis: |
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* |
| Â | 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 |
(s)
where μ, and σ are the mean, and the standard deviation of the cough airflow signal respectively.
where μ, and σ are the mean, and the standard deviation of the cough airflow signal respectively.