Sound transmission in the chest under surface excitation: an experimental and computational study with diagnostic applications
Abbreviated Journal Title
Med. Biol. Eng. Comput.
Computational modeling; Lung acoustics; Pneumothorax; Percussion; Human; studies; MAGNETIC-RESONANCE ELASTOGRAPHY; PULMONARY ACOUSTIC TRANSMISSION; AUSCULTATORY PERCUSSION; MR ELASTOGRAPHY; PNEUMOTHORAX; LUNG; SYSTEM; MODEL; Computer Science, Interdisciplinary Applications; Engineering, ; Biomedical; Mathematical & Computational Biology; Medical Informatics
Chest physical examination often includes performing chest percussion, which involves introducing sound stimulus to the chest wall and detecting an audible change. This approach relies on observations that underlying acoustic transmission, coupling, and resonance patterns can be altered by chest structure changes due to pathologies. More accurate detection and quantification of these acoustic alterations may provide further useful diagnostic information. To elucidate the physical processes involved, a realistic computer model of sound transmission in the chest is helpful. In the present study, a computational model was developed and validated by comparing its predictions with results from animal and human experiments which involved applying acoustic excitation to the anterior chest, while detecting skin vibrations at the posterior chest. To investigate the effect of pathology on sound transmission, the computational model was used to simulate the effects of pneumothorax on sounds introduced at the anterior chest and detected at the posterior. Model predictions and experimental results showed similar trends. The model also predicted wave patterns inside the chest, which may be used to assess results of elastography measurements. Future animal and human tests may expand the predictive power of the model to include acoustic behavior for a wider range of pulmonary conditions.
Medical & Biological Engineering & Computing
"Sound transmission in the chest under surface excitation: an experimental and computational study with diagnostic applications" (2014). Faculty Bibliography 2010s. 5943.