abstract = {Purpose: Lung auscultation has long been a standard of care for the diagnosis of respiratory diseases. Recent advances in electronic auscultation and signal processing have yet to find clinical acceptance; however, computerized lung sound analysis may be ideal for pediatric populations in settings, where skilled healthcare providers are commonly unavailable. We described features of normal lung sounds in young children using a novel signal processing approach to lay a foundation for identifying pathologic respiratory sounds. Methods: 186 healthy children with normal pulmonary exams and without respiratory complaints were enrolled at a tertiary care hospital in Lima, Peru. Lung sounds were recorded at eight thoracic sites using a digital stethoscope. 151 (81 {\%}) of the recordings were eligible for further analysis. Heavy-crying segments were automatically rejected and features extracted from spectral and temporal signal representations contributed to profiling of lung sounds. Results: Mean age, height, and weight among study participants were 2.2 years (SD 1.4), 84.7 cm (SD 13.2), and 12.0 kg (SD 3.6), respectively; and, 47 {\%} were boys. We identified ten distinct spectral and spectro-temporal signal parameters and most demonstrated linear relationships with age, height, and weight, while no differences with genders were noted. Older children had a faster decaying spectrum than younger ones. Features like spectral peak width, lower-frequency Mel-frequency cepstral coefficients, and spectro-temporal modulations also showed variations with recording site. Conclusions: Lung sound extracted features varied significantly with child characteristics and lung site. A comparison with adult studies revealed differences in the extracted features for children. While sound-reduction techniques will improve analysis, we offer a novel, reproducible tool for sound analysis in real-world environments.},
author = {Ellington, Laura E. and Emmanouilidou, Dimitra and Elhilali, Mounya and Gilman, Robert H. and Tielsch, James M. and Chavez, Miguel A. and Marin-Concha, Julio and Figueroa, Dante and West, James and Checkley, William},
doi = {10.1007/s00408-014-9608-3},
issn = {0341-2040},
journal = {Lung},
keywords = {Child,Diagnosis,Electronic auscultation,Filterbank,Power spectrum,Spectro-temporal analysis,Time–frequency analysis},
number = {5},
pages = {765--773},
title = {{Developing a Reference of Normal Lung Sounds in Healthy Peruvian Children}},
url = {http://link.springer.com/10.1007/s00408-014-9608-3},
volume = {192},
year = {2014}