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

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.

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.