Automatic Wheeze Detection and Lung Function Evaluation - A Preliminary Study

Ana Oliveira, Cátia Pinho, João Dinis, Daniela Oliveira, Alda Marques


The automatic detection of wheeze offers the potential for diagnosing and monitoring respiratory diseases, e.g., lower respiratory tract infection (LRTI). By determining the relationship between wheeze detection and other lung function data, it is possible to develop a more sensitive tool for detecting respiratory conditions. This pilot study aimed to: i) explore the robustness of a time frequency wheeze detector (TF-WD) and ii) describe the correlation between wheezing and spirometry parameters. Lung sounds and spirometry parame-ters were acquired from six outpatients with LRTI (five with right lung infection). Number, fundamental frequency and duration of wheezes were obtained through a TF-WD algorithm. The performance of the TF-WD algorithm was evaluated by comparing its findings in 40 files with those annotated by two experts. Re-sults suggest that the TF-WD algorithm is an efficient and robust method for computerised wheeze detection in LRTI (SE=72.5%; SP=99.2%). Furthermore, significant correlations were found between the percentage predicted of forced expiratory volume in 1 second and forced vital capacity (FEV1pp and FVCpp) and wheeze duration at lateral (rs=-0.9, p=0.03) and posterior (rs=-0.9, p=0.01) right regions respectively. These results support the use of pulmonary auscultation and spirometry to detect areas of obstruction in LRTI.


  1. Dinis, J., Campos, G., Rodrigues, J. & Marques, A. Year. Respiratory Sound Annotation Software. In: International Conference on Health Informatics, 2012 Vilamoura, Portugal. Proceedings of HEALTHINF 2012 - International Conference on Health Informatics, 183-188.
  2. Earis, J. & Cheetham, B. 2000. Future perspectives for respiratory sound research. European Respiratory Review, 10 641-646.
  3. Gabor, D. 1946. Theory of communication. IEEE, 93, 429-457.
  4. Guntupalli, K. K., Alapat, P. M., Bandi, V. D. & Kushnir, I. 2008. Validation of automatic wheeze detection in patients with obstructed airways and in healthy subjects. Journal of asthma, 45, 903-7.
  5. Leuppi, J. D., Dieterle, T., Wildeisen, I., Martina, B., Tamm, M., Koch, G., Perruchoud, A. P. & Leimenstoll, B. M. 2006. Can airway obstruction be estimated by lung auscultation in an emergency room setting? Respiratory Medicine, 100, 279-285.
  6. Lieberman, D., Korsonsky, I., Ben-Yaakov, M., Lazarovich, Z., Friedman, M. G., Dvoskin, B., Leinonen, M., Ohana, B. & Boldur, I. 2002. A comparative study of the etiology of adult upper and lower respiratory tract infections in the community. Diagnostic microbiology and infectious disease, 42, 21-8.
  7. Marques, A., Bruton, A. & Barney, A. 2006. Clinically useful outcome measures for physiotherapy airway clearance techniques: a review. Physical Therapy Reviews, 11, 299-307.
  8. Marques, A., Bruton, A. & Barney, A. 2009. Reliability of lung crackle characteristics in cystic fibrosis and bronchiectasis patients in a clinical setting. Physiological Measurement, 30, 903-912.
  9. Meslier, N., Charbonneau, G. & Racineux, J. L. 1995. Wheezes. European respiratory journal, 8, 1942-8.
  10. Miller, M. R. 2005. Standardisation of spirometry. European Respiratory Journal, 26, 319-338.
  11. Oliveira, D., Pinho, C., Marques, A. & Dinis, J. 2011. Validation of a time-frequency wheeze detector in cystic fibrosis: a pilot study. European Respiratory Journal, 38, 237s.
  12. Oud, M., Dooijes, E. H. & van der Zee, J. S. 2000. Asthmatic airways obstruction assessment based on detailed analysis of respiratory sound spectra. IEEE transactions on bio-medical engineering, 47, 1450-5.
  13. Paciej, R., Vyshedskiy, A., Bana, D. & Murphy, R. 2004. Squawks in pneumonia. Thorax, 59, 177-178.
  14. Rossi, M., Sovijärvi, A. R. A., Piirilä, P., Vannuccini, L., Dalmasso, F. & Vanderschoot, J. 2000. Environmental and subject conditions and breathing manoeuvres for respiratory sound recordings. European Respiratory Review, 10, 611-615.
  15. Sovijärvi, A., Dalmasso, F., Vanderschoot, J., Malmberg, L., Righini, G. & Stoneman, S. 2000. Definition of terms for applications of respiratory sounds. European Respiratory Review, 10, 597-610.
  16. Taplidou, S. A. & Hadjileontiadis, L. J. 2007. Wheeze detection based on time-frequency analysis of breath sounds. Computers in Biology and Medicine, 37, 1073-1083.
  17. Woodhead, M., Blasi, F., Ewig, S., Garau, J., Huchon, G., Ieven, M., Ortqvist, A., Schaberg, T., Torres, A., van der Heijden, G., Read, R. & Verheij, T. J. 2011. Guidelines for the management of adult lower respiratory tract infections--full version. Clinical Microbiology and Infection, 17 Suppl 6, E1-59.
  18. World Health Organization 2008. The global burden of disease - 2004 update Switzerland: World Health Organization.

Paper Citation

in Harvard Style

Oliveira A., Pinho C., Dinis J., Oliveira D. and Marques A. (2013). Automatic Wheeze Detection and Lung Function Evaluation - A Preliminary Study . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2013) ISBN 978-989-8565-37-2, pages 323-326. DOI: 10.5220/0004191903230326

in Bibtex Style

author={Ana Oliveira and Cátia Pinho and João Dinis and Daniela Oliveira and Alda Marques},
title={Automatic Wheeze Detection and Lung Function Evaluation - A Preliminary Study},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2013)},

in EndNote Style

JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2013)
TI - Automatic Wheeze Detection and Lung Function Evaluation - A Preliminary Study
SN - 978-989-8565-37-2
AU - Oliveira A.
AU - Pinho C.
AU - Dinis J.
AU - Oliveira D.
AU - Marques A.
PY - 2013
SP - 323
EP - 326
DO - 10.5220/0004191903230326