Extract
The ability to measure cough frequency from sound recordings has changed the standards by which new cough treatments are evaluated and is providing insights into the mechanisms underlying cough in respiratory disease [1–5]. Objective measures of the number of coughs over extended time periods can be made using off-the-shelf sound recording devices, with aural counting of cough sounds captured. Although excellent inter-observer agreement can be achieved, this process is extremely laborious and limits the size and scope of possible studies [6, 7]; thus, there is a need for more efficient cough quantification methods. Accurate cough detection is, however, complicated by the substantial variability in cough acoustics both within and between individuals. There is also the challenge of distinguishing cough from large amounts of speech and an infinite array of environmental noises that may be captured during ambulatory sound recordings. Indeed, fully automated cough detection systems have failed to achieve sufficient accuracy to be useful, despite apparent success in preliminary tests [8, 9]. A semi-automated algorithm is in use in clinical studies but has only undergone preliminary validation, reporting modest sensitivity in small numbers of individuals (82.3–86%) in recordings made by a now obsolete mp3 player/recorder [10, 11]. The influence of user input, and the robustness of this algorithm to detect cough in different respiratory diseases and in recordings made using different recording devices with different acoustic encoding have not been assessed.
Abstract
The VitaloJAK filtering algorithm has undergone the most extensive testing of any cough monitoring software and is sensitive/efficient across a range of diagnoses and age groups, and in recordings containing a wide range of cough counts https://bit.ly/3rF9vp1
Footnotes
Author contributions: J.A. Smith drafted the manuscript and analysed the data; K. McGuinness developed the algorithm; K. Holt and R. Dockry were involved in data collection and cough counting; S. Sen, K. Sheppard, P. Turner and P. Czyzyk performed cough counting. All authors reviewed and contributed to the final manuscript.
Data availability: De-identified cough recording data from this study will be shared, following publication, with researchers following review by the steering committee of the research database. Proposals for access should be directed to kimberley.holt@manchester.ac.uk
Conflict of interest: J.A. Smith reports non-financial support (provision of equipment) from Vitalograph Ltd, during the conduct of the study; grants and personal fees for consultancy from Merck, Bayer, Bellus, Shionogi, Nerre, Nocion and Axalbion, personal fees for consultancy from Attenua, Menlo, Boehringer Ingelheim and Algernon, grants from GSK, outside the submitted work; and has a patent Cough detection with royalties paid to her hospital.
Conflict of interest: K. Holt has nothing to disclose.
Conflict of interest: R. Dockry has nothing to disclose.
Conflict of interest: S. Sen has nothing to disclose.
Conflict of interest: K. Sheppard has nothing to disclose.
Conflict of interest: P. Turner has nothing to disclose.
Conflict of interest: P. Czyzyk has nothing to disclose.
Conflict of interest: K. McGuinness reports non-financial support (provision of equipment) from Vitalograph Ltd, during the conduct of the study; has a patent Cough detection with royalties paid; and invented the VitaloJAK filtering algorithm which has been licensed by Manchester University Foundation Trust and the University of Manchester to Vitalograph Ltd and Vitalograph Ireland (Ltd); Manchester University Foundation Trust receives royalties which may be shared with K. McGuinness as the inventor and the clinical division in which J.A. Smith works.
Support statement: This work was jointly funded by NIHR Manchester Biomedical Research Centre (J.A. Smith, K. Holt and K. McGuinness) and Wellcome Investigator Award (R. Dockry and K. McGuinness) (207504/B/17/Z). J.A. Smith is an NIHR Senior Investigator. Funding information for this article has been deposited with the Crossref Funder Registry.
- Received November 23, 2020.
- Accepted March 25, 2021.
- Copyright ©The authors 2021. For reproduction rights and permissions contact permissions{at}ersnet.org