![]() ![]() On the contrary, the understanding of mechanisms linked to the creation of breath sounds is, for the moment, imperfect. It can be inferred from these studies that the validation of automatic crackles detection algorithms should not take auscultation as unique reference. Type of crackles: fine crackles are easily recognizable in so far as their waveform differs more from the waveform of classical lung sounds, ![]() Intensity of the respiratory signal: deep breaths mask more crackles than superficial breaths, The results indicate that the most important detection errors are due to the following factors: The methods used consist in simulated crackles superimposed on real breath sound. Studies were performed in order to test the human's ear capability to detect crackles in an auscultation signal. Thus, the spectral density and amplitude of sounds can indicate the state of the lungs parenchyma, the dimension of the airways and their pathological modification. Respiratory sounds include invaluable information concerning the physiologies and pathologies of lungs and airways obstruction. Keywords: state of the art, auscultation, respiratory sounds, crackles, wheezes, respiratory phase detection, spectral analysis, wavelet, respiratory phase classification, signal processing, artificial neural networks, genetic algorithm, multilayer perceptron, fuzzy rule base identification systemĭistinction between normal respiratory sounds and abnormal ones (such as crackles, wheezes.) is important for an accurate medical diagnosis. Modern tools are based on artificial intelligence and on technics such as artificial neural networks, fuzzy systems, and genetic algorithms.Ĭonclusion: The next step will consist in finding new markers so as to increase the efficiency of decision aid algorithms and tools. Results: 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. Methods and material: Review of the current medical and technological literature using Pubmed and personal experience. Objective: This paper describes state of the art, scientific publications and ongoing research related to the methods of analysis of respiratory sounds. 4M.D., Ph.D., Head of the Internal Medicine Department, Clinique Médicale B, CHRU Strasbourg, Strasbourg, France. ![]() 3M.D., Head of the Cardiology Department, Clinique Médicale B, CHRU Strasbourg, Strasbourg, France. 2Technical Academy Fellow, Alcatel-Lucent, Chief Technical Office, Strasbourg, France. Sandra Reichert1, Raymond Gass2, Christian Brandt3 and Emmanuel Andrès4ġPh.D., e-health UTBM student, Alcatel-Lucent, Chief Technical Office, Strasbourg, France. Analysis of Respiratory Sounds: State of the Art ![]()
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