Abstract Background: Cough is extremely common in childhood and a tool to objectively measure cough frequency would be clinically beneficial. To date paediatric cough monitoring systems have relied on manual cough counting which is time consuming and costly. The VitaloJAKâ¢ (Vitalograph, UK) is a custom built 24hr semi-automated cough monitoring device that has been used successfully to quantify cough in adults. This thesis consists of a series of studies using the VitaloJAKâ¢ monitor system in children. Methods: Firstly, we tested the feasibility of using the VitaloJAKâ¢ for 24 hr cough recordings in children and tested existing compression software for cough quantification. The VitaloJAKâ¢ system was then used to to assess and compare the cough frequency, variation and circadian distribution of cough in children with asthma, CF, and PCD during stable periods of disease and during an exacerbation. Finally, we used modelling to assess whether cough events are random events, or are clustered in time; the time intervals between coughs for each patient were calculated and fitted to an exponential model of random recurrences and a Weibull model for clustered recurrences. Results: The majority of children were able to wear the monitor for almost 24 hours without too much difficulty; overall, children wore the monitor for a median of 22.25 hours (0.38 â 24hrs). Using the compression software, a median of 100% (91-100) of coughs was retained and 24-hour records were reduced down to around 10% of their original size. There was no significant difference in cough frequency between the three disease groups. The median (range) cough frequency per hour was 3 (0.2 to 18) coughs/hour (c/h), 4 (0.5 to 37) c/h, and 4 (0.5 to 27) c/h for asthma, CF, and PCD groups respectively (p=0.3). Cough frequency in children was significantly greater during the day and reduced during sleep in all disease groups. There was a significant difference in the 24-hour cough frequency between the exacerbation and stable asthma group (median 11 (0-27) vs. 3 (0-5), p=0.004). The 24-hour pattern revealed a substantial variability in peak timing of cough in each respiratory disease. Children with asthma peaked in the early evening, those with CF in the morning, and those with PCD in the afternoon. No difference was found in the circadian cough rate, when divided into 6 4-hour time periods, either between the three diseases (p=0.18) or between stable and exacerbation phases among the asthmatic children (p=0.14). A significant difference was seen in the 24-hour total cough frequency between asthmatic children (median 4c/h; range 1-18) and adults (median 1 c/h; range 0.3-16); p=0.001. The temporal pattern of recurrence of cough events is non-randomly distributed over time, and this was best described by the Weibull model in the majority of the 24hr cough, day-time cough and night-time cough recordings in children and adults. The cough events appear to cluster together in time, with the probability of a second cough being initially high and decreasing with time. Conclusion: This thesis has demonstrated that the VitaloJAKâ¢ semi-automated cough monitor provides an accurate estimate of cough frequency in children (sensitivity 100%) while significantly reducing the time required for analysis. A substantial variability in the timing of peak cough frequency exists in each respiratory disease and this might reflect different mechanisms of cough in each disease. Sleep appears to significantly reduce cough in all the diseases studied, both when disease is stable and exacerbating. In both asthmatic children and adults, the recurrence pattern of coughs is clustered and can be described by a Weibull distribution. This work has set a foundation for further investigation of the cough frequency and 24 hour cough circadian patterns in children.