Abstract
This paper describes state of the art, scientific publications and ongoing research related to the methods of analysis of respiratory sounds. Review of the current medical and technological literature using Pubmed and personal experience. The study includes a description of the various techniques that are being used to collect auscultation sounds, a physical description of known pathologic sounds for which automatic detection tools were developed. Modern tools are based on artificial intelligence and on technics such as artificial neural networks, fuzzy systems, and genetic algorithms… The next step will consist in finding new markers so as to increase the efficiency of decision aid algorithms and tools.
Highlights
Distinction between normal respiratory sounds and abnormal ones is important for an accurate medical diagnosis
The methods used consist in simulated crackles superimposed on real breath sound
Artificial neural network (ANN): it is a mathematical model based on biological neural networks
Summary
The study includes a description of the various techniques that are being used to collect auscultation sounds, a physical description of known pathologic sounds for which automatic detection tools were developed. Modern tools are based on artificial intelligence and on technics such as artificial neural networks, fuzzy systems, and genetic algorithms
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