#### Daddy07

##### Newbie level 4

I'm in a situation....

I need to analyse lung sounds samples to detect crackles present in them and further classify these crackles by their characteristics for a project.

Having read some articles that have done such analysis, I figured the wavelet toolbox in MATLAB is the best tool for this purpose.

Problem is, with my mechanical engineering background, I have limited understanding of the algorithms and techniques actually used.

I have been playing around with the Wavelet Toolbox and also the DSP Toolbox in Simulink to see if I can get anywhere but keep coming to dead ends.

What I think I have picked up is:

-The wavelet type I'm trying to pick up is the debauchies type 8 (db8).

-To use Wavelet Packet Transform to differentiate the stationary and non-stationary components of the original signal.

-The stationary signals are the crackle signals that I would later classify, and these have to be rebuilt by Inverse Wavelet Packet transform.

-There are levels in a wavelet decomposition tree (of which I need 5 for this purpose)

-A pair of FIR filters are used in WPT, but I am not sure what the settings for these filters are, except that one is a high-pass and the other a low-pass, with both having same cut-off frequency.

-Input signal may need to a 2

^{n}(?). My .wav sound files are 11025Hz.

-Some coefficients are involved, but am not exactly sure about these.

I have almost no code programming knowledge, so I'd prefer to do these in Simulink or using the MATLAB Wavelet Toolbox.

The part above is only for separating my crackle sounds from the lung sounds, but I'd be extremely grateful if someone could hold my hand through this and hopefully, lay some foundation for me to figure out the next part of the analysis.

Thank you in advance.