Method and apparatus for performing dynamic respiratory classification and tracking of wheeze and crackle

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 detecting wheeze from an audio respiratory signal, the method comprising:

• capturing the audio respiratory signal generated by a subject using a microphone;
• recognizing a plurality of breath cycles and a plurality of breath phases from the audio respiratory signal;
• detecting wheezing from the plurality of breath cycles and the plurality of breath phases, wherein the detecting comprises:
• analyzing a block of interest in the audio respiratory signal, wherein the block of interest comprises a plurality of frames;
• calculating an auto-correlation function (ACF) for each frame in the block of interest;
• determining a maximum value of the ACF calculated for each frame in the block of interest;
• and
• analyzing the maximum value to detect if wheezing is present in the block of interest, wherein the analyzing comprises determining if the maximum value is greater than a first predetermined threshold, wherein the first predetermined threshold is based on an empirically determined value;
• responsive to a determination that the maximum value is less than the first predetermined threshold but above a second predetermined threshold, categorizing the block of interest as associated with tension in the subject;
• and
• responsive to a determination that the maximum value is greater than the first predetermined threshold, categorizing the block of interest as associated with wheezing in the subject.

A system for detecting wheeze 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 configured to operate in accordance with said application to:
• recognize a plurality of breath cycles and a plurality of breath phases from the audio respiratory signal;
• detect wheezing from the plurality of breath cycles and the plurality of breath phases, wherein the detect wheezing is performed by the process which is configured to:
• analyze a block of interest in the audio respiratory signal, wherein the block of interest comprises a plurality of frames;
• calculate an auto-correlation function (ACF) for each frame in the block of interest;
• determine a maximum value of the ACF calculated for each frame in the block of interest;
• analyze the maximum value to detect if wheezing is present in the block of interest, wherein to analyze the maximum value, the processor is further configured to determine if the maximum value is greater than a first predetermined threshold, wherein the first predetermined threshold is based on an empirically determined value;
• responsive to a determination that the maximum value is less than the first predetermined threshold but above a second predetermined threshold, categorizing the block of interest as associated with tension in the subject;
• and
• responsive to a determination that the maximum value is greater than the first predetermined threshold, categorizing the block of interest as associated with wheezing in the subject.