Developing a Reference of Normal Lung Sounds in Healthy Peruvian Children

Laura E. Ellington, Dimitra Emmanouilidou, Mounya Elhilali, Robert H. Gilman, James M. Tielsch, Miguel A. Chavez, Julio Marin-Concha, Dante Figueroa, James West, William Checkley

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


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.

Original languageEnglish
Pages (from-to)765-773
Number of pages9
Issue number5
StatePublished - Oct 1 2014


  • Child
  • Diagnosis
  • Electronic auscultation
  • Filterbank
  • Power spectrum
  • Spectro-temporal analysis
  • Time–frequency analysis


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