Method and apparatus for performing dynamic respiratory classification and analysis for detecting wheeze particles and sources

1. A method for analyzing an audio respiratory signal, the method comprising:

capturing the audio respiratory signal from a subject using a microphone;

partitioning the audio respiratory signal into a plurality of overlapping frames and a plurality of non-overlapping frames;

calculating a fourier transform for each frame;

determining a magnitude spectrum using the fourier transform of the plurality of overlapping frames;

extracting a spectrogram using the magnitude spectrum;

analyzing the spectrogram to determine characteristics pertaining to wheeze sounds in the audio respiratory signal;

creating an artificial crackle comprising a filtered impulse response frame created by filtering a delta function;

calculating a cross correlation function between each of the non-overlapping frames and the artificial crackle;

determining if the cross correlation function exceeds a predetermined threshold; and

responsive to a determination that the cross correlation function exceeds the predetermined threshold, identifying a respective frame for which the cross correlation function exceeds the predetermined threshold as associated with crackling.

2. The method of claim 1 , wherein the artificial crackle is created by filtering the delta function in the filtered impulse response frame with a narrow IIR bandpass filter.

3. The method of claim 1 , further comprising:

storing a timestamp and intensity corresponding to each frame identified as associated with crackling; and

extracting a plurality of characteristics pertaining to crackling using frames identified as associated with crackling.

4. The method of claim 1 , further comprising:

extracting a magnified spectrogram using the spectrogram, wherein the magnified spectrogram is operable to determine a number of wheeze particles.

5. The method of claim 1 , further comprising:

extracting an interpolated spectrogram using the spectrogram, wherein the interpolated spectrogram is operable to provide a clearer view of wheeze particles by subtracting out residual airflow energies from the spectrogram.

6. The method of claim 1 , wherein the analyzing further comprises:

executing an edge-detection procedure on the spectrogram to highlight wheeze particles in the spectrogram.

7. The method of claim 6 , wherein the analyzing further comprises:

for each column in the spectrogram, performing the following:

(a) store locations of elements with high values resulting from the edge-detection procedure into a vector;

(b) compare a location of the first element in the vector with locations of remaining elements in the vector;

(c) designate any of the remaining elements where a respective location is a multiple of the location of the first element as a harmonic of the first element; and

(d) repeat steps a), b) and c) for each element in the vector.

8. A non-transitory computer-readable storage medium having stored thereon, computer executable instructions that, if executed by a computer system cause the computer system to perform a method for analyzing an audio respiratory signal, the method comprising:

capturing the audio respiratory signal from a subject using a microphone;

partitioning the audio respiratory signal into a plurality of overlapping frames and a plurality of non-overlapping frames;

calculating a fourier transform for each frame;

extracting a spectrogram using the fourier transform of the plurality of overlapping frames;

analyzing the spectrogram to determine characteristics pertaining to wheeze sounds in the audio respiratory signal;

creating an artificial crackle comprising a filtered impulse response frame created by filtering a delta function;

calculating a cross correlation function between each of the non-overlapping frames and the artificial crackle;

determining if the cross correlation function exceeds a predetermined threshold; and

responsive to a determination that the cross correlation function exceeds the predetermined threshold, identifying a respective frame for which the cross correlation function exceeds the predetermined threshold as associated with crackling.

9. The non-transitory computer-readable storage medium of claim 8 , wherein the artificial crackle is created by filtering the delta function in the filtered impulse response frame with a narrow IIR bandpass filter.

10. The non-transitory computer-readable storage medium of claim 8 , wherein the method further comprises:

storing a timestamp and intensity corresponding to each frame identified as associated with crackling; and

extracting a plurality of characteristics pertaining to crackling using frames identified as associated with crackling.

11. The non-transitory computer-readable storage medium of claim 8 , wherein the method further comprises:

extracting a magnified spectrogram using the spectrogram, wherein the magnified spectrogram is operable to determine a number of wheeze particles.

12. The non-transitory computer-readable storage medium of claim 8 , wherein the method further comprises:

extracting an interpolated spectrogram using the spectrogram, wherein the interpolated spectrogram is operable to provide a clearer view of wheeze particles by subtracting out residual airflow energies from the spectrogram.

13. A system for detecting wheeze and crackle from an audio respiratory signal, the system comprising:

a spirometer comprising a first microphone, wherein the first microphone is operable to capture the audio respiratory signal from a subject;

a memory coupled to the spirometer and operable to store the audio respiratory signal, wherein the memory further comprises an application for detecting wheeze and crackle from a breathing session stored therein; and

a processor coupled to said memory and said spirometer, the processor being configured to operate in accordance with said application to:

capture the audio respiratory signal from a subject using a microphone;

partition the audio respiratory signal into a plurality of overlapping frames and a plurality of non-overlapping frames;

calculate a fourier transform for each frame;

determine a magnitude spectrum using the fourier transform of the plurality of overlapping frames;

extract a spectrogram using the magnitude spectrum;

analyze the spectrogram to determine characteristics pertaining to wheeze sounds in the audio respiratory signal;

create an artificial crackle comprising a filtered impulse response frame created by filtering a delta function;

calculate a cross correlation function between each of the non-overlapping frames and the artificial crackle;

determine if the cross correlation function exceeds a predetermined threshold; and

responsive to a determination that the cross correlation function exceeds the predetermined threshold, identify a respective frame for which the cross correlation function exceeds the predetermined threshold as associated with crackling.

14. The system of claim 13 , wherein the artificial crackle is created by filtering the delta function in the filtered impulse response frame with a narrow IIR bandpass filter.

15. The system of claim 13 , wherein the processor is further configured to:

store a timestamp and intensity corresponding to each frame identified as associated with crackling; and

extract a plurality of characteristics pertaining to crackling using frames identified as associated with crackling.

16. The system of claim 13 , wherein the processor is further configured to:

extract a magnified spectrogram using the spectrogram, wherein the magnified spectrogram is operable to determine a number of wheeze particles.

17. The system of claim 13 , wherein the processor is further configured to:

extract an interpolated spectrogram using the spectrogram, wherein the interpolated spectrogram is operable to provide a clearer view of wheeze particles by subtracting out residual airflow energies from the spectrogram.