Background A hallmark of many respiratory conditions is the presence of nocturnal symptoms. Nevertheless, especially in children there is currently still a huge diagnostic gap in detecting nighttime symptoms, which leads to an underestimation of the frequency in clinical practise. Methods We evaluated the clinical applicability and determined the formal test characteristics of the LEOSound (R) system, a device for digital long-time recording and automated detection of acoustic airway events. Airway sounds were recorded overnight in 115 children and adolescents (1-17 years) with and without respiratory conditions. The automated classification for "cough" and "wheezing" was subsequently validated against the manual acoustic reassessment by an expert physician. Results The general acceptance was good across all age groups and a technically successful recording was obtained in 98 children, corresponding to 92,976 sound epochs (a 30 s) or a total of 774 h of lung sounds. We found a sensitivity of 89% and a specificity of 99% for the automated detection of cough. For detection of wheezing, sensitivity and specificity were both 98%. The cough index and the wheeze index (events per hour) of individual patients showed a strong positive correlation (cough: r(S) = 0.85, wheeze: r(S) = 0.95) and a sufficient agreement of the two assessment methods in the Bland-Altman analysis. Conclusion Our data show that the LEOSound (R) is a suitable device for standardized detection of cough and wheezing and hence a promising diagnostic tool to detect nocturnal respiratory symptoms, especially in children. However, a validation process to reduce false positive classifications is essential in clinical routine use.