Spatial distribution of normal lung sounds in healthy individuals under varied inspiratory load and flow conditions
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
Respiratory sounds yield pertinent information about respiratory function in both health and disease. Normal lung sound intensity is a characteristic that correlates well with airflow and it can therefore be used to quantify the airflow changes and limitations imposed by respiratory diseases. The dual aims of this study are firstly to establish whether previously reported asymmetries in normal lung sound intensity are affected by varying the inspiratory threshold load or the airflow of respiration, and secondly to investigate whether fixed sample entropy can be used as a valid measure of lung sound intensity. Respiratory sounds were acquired from twelve healthy individuals using four contact microphones on the posterior skin surface during an inspiratory threshold loading protocol and a varying airflow protocol. The spatial distribution of the normal lung sounds intensity was examined. During the protocols explored here the normal lung sound intensity in the left and right lungs in healthy populations was found to be similar, with asymmetries of less than 3 dB. This agrees with values reported in other studies. The fixed sample entropy of the respiratory sound signal was also calculated and compared with the gold standard root mean square representation of lung sound intensity showing good agreement.
CitationLozano, M. [et al.]. Spatial distribution of normal lung sounds in healthy individuals under varied inspiratory load and flow conditions. A: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. "EMBC'20: 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: 20-24 July 2020: Montreal, Canada". Institute of Electrical and Electronics Engineers (IEEE), p. 1-4. ISBN 978-1-7281-1991-5. DOI 10.1109/EMBC44109.2020.9175992.