I have used neural networks for classification and represented the breath sounds by using their frequency spectrum. Read the abstract or download a zipped postscript file of the entire master's thesis . The results have been published in the Journal of Clinical Monitoring and Computing . The abstract is here . I think future efforts in this area should focus on the calculation of a transfer function between the trachea and the lower lung and seeing if this transfer function changes as a result of lung pathology.
Patients often have several abnormalities such as crackles and wheezes.
Unavoidable background noise in the ICU from bedside monitors, motion, TVs, staff, and visitors. Instability in the recording technology when compared to other biomedical sensors. Sometimes a sound that is pathological in one patient might be considered normal in another. For instance, a relatively healthy patient who is ventilated will have breath sounds that are so quiet they might be considered pathological in another patient. I feel the best book on this topic is Breath Sounds Methodology by Noam Gavriely.