Lung auscultation using smartphone built-in microphone versus digital stethoscope: a comparative early feasibility study.

Background: Lung auscultation using a smartphone built-in microphone is promising for home monitoring of pediatric respiratory diseases. Our aim was to compare respiratory sounds recorded by a smartphone and a digital stethoscope by assessing the proportion of quality recordings and adventitious sounds detected by each device.

Methods: A comparative early feasibility study with children from a public school in Northern Portugal was conducted. Lung auscultation was performed at 7 locations (trachea, anterior superior, posterior superior, and posterior inferior regions of both hemithoraces). Two researchers recorded lung auscultation simultaneously with a smartphone and a digital stethoscope, and independently classified recordings regarding their quality (at least one respiratory cycle audible with minimal artefacts) and presence of adventitious sounds. A third researcher resolved the disagreements. Proportions of sounds with quality and with adventitious sounds were compared between devices using chi-square tests. Inter-device agreement was also assessed with proportion of agreement and Cohen kappa.

Results: Twenty-seven children (20 male, 10.2±0.6 years) were enrolled, 8 had self-reported asthma. A total of 378 respiratory sounds (smartphone N.=190, digital stethoscope N.=188 [2 missing]) were recorded. The percentage of recordings with quality was high in both devices (93% smartphone vs. 97% digital stethoscope, P=0.065). Adventitious sounds were identified in 11% and 19% of the recordings acquired with smartphone and digital stethoscope, respectively (P=0.021). The overall inter-device proportion of agreement for the presence of adventitious sounds was 90% (kappa 0.60, 95%CI 0.42, 0.77).

Conclusions: Smartphone lung auscultation seems to be a viable technology for recording respiratory sounds and identifying adventitious sounds in children. Further research is needed to validate its potential for effective remote respiratory disease monitoring.