Advertisement

Speech signal analysis as an alternative to spirometry in asthma diagnosis: investigating the linear and polynomial correlation coefficient

  • John KutorEmail author
  • Srinivasan Balapangu
  • Jeromy K. Adofo
  • Albert Atsu Dellor
  • Christopher Nyakpo
  • Godfred Akwetey Brown
Article
  • 4 Downloads

Abstract

Speech production involves the vibration of the vocal cords. Voice changes will occur in respiratory diseases such as asthma due to the inflamed lung airways, which is part of the vocal tract. Spirometry is a well-known technique employed in diagnosis of asthma to give information on patient pulmonary function. The purpose of this research was to investigate the correlation between Forced Expiratory Volume to Forced Vital Capacity (FEV1/FVC) ratio obtained from spirometry and Harmonics-to-Noise Ratio (HNR) obtained from human speech, in order to determine whether speech analysis could be an alternative to spirometry in diagnosing asthma. Spirometry data was obtained from 150 subjects, who were asthmatic patients attending the Korle-Bu Teaching Hospital, Ghana. Speech data consisting of the vowel sounds /a:/,/e:/, /ɛ:/, /i:/,/o:/, /ɔ:/,/u:/ and phrase “She sells”, was also recorded from the subjects. 33 samples were selected and analyzed to generate speech parameters with Praat software. Correlation was established between HNR from the speech signals and spirometry data FEV1/FVC. The highest correlation coefficient was observed between HNR and vowel sound /ɛ:/ (42.08%). In conclusion, among the other speech vowels and phonemes, HNR of /ɛ:/ sound showed the most promise to being a suitable marker in using speech as an alternative to spirometry in asthma diagnosis.

Keywords

Harmonics-to-noise ratio FEV1 FVC Asthma Speech Diagnosis 

Notes

Acknowledgements

The authors would like to acknowledge the contribution of all who have in one way or the other aided in some aspects of this work especially, Dr. Audrey Forson of University of Ghana Medical School, Dr. Asomani of Chest Department, Korle-Bu, Ms. Beatrice Adom, Mr. Emmanuel Offei and Mr. Obed Korshie Dzikunu of the Department of Biomedical Engineering, University of Ghana. This work is fully funded by Office of Research and Innovation Development (ORID), University of Ghana. Grant Ref: ORID/ILG/-019/05-13.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Informed consent

Informed consent was obtained from all participants of the study before including them in the study.

References

  1. Batra, K., Bhasin, S., & Singh, A. (2015a). Acoustic analysis of voice samples to differentiate healthy and asthmatic persons. International Journal of Engineering and Computer Science, 4(7), 13161–13164.Google Scholar
  2. Batra, K., Bhasin, S., & Singh, A. (2015b). Comparison of asthma and healthy persons using voice analysis. International Journal of Engineering Sciences & Research Technology, 4(7), 928–932.Google Scholar
  3. Bousquet, J., Khaltaev, N. G., & Cruz, A. A. (2007). Global surveillance, prevention and control of chronic respiratory diseases: A comprehensive approach. Geneva: World Health Organization.Google Scholar
  4. Dixit, V. M., & Sharma, Y. (2014). Voice parameter analysis for the disease detection. IOSR Journal of Electronics and Communication Engineering, eISSN, 9(3), 48–55.CrossRefGoogle Scholar
  5. Farrús, M., Hernando, J., & Ejarque, P. Jitter and shimmer measurements for speaker recognition. In Eighth annual conference of the international speech communication association, 2007.Google Scholar
  6. Honda, M. (2003). Human speech production mechanisms. NTT Technical Review, 1(2), 24–29.Google Scholar
  7. Mohamed, E. E. (2014). Voice changes in patients with chronic obstructive pulmonary disease. Egyptian Journal of Chest Diseases and Tuberculosis, 63(3), 561–567.CrossRefGoogle Scholar
  8. Network, G. A. (2014). The global asthma report 2014. Auckland, New Zealand. p. 769.Google Scholar
  9. Sahebjami, H., & Gartside, P. S. (1996). Pulmonary function in obese subjects with a normal FEV1/FVC ratio. Chest, 110(6), 1425–1429.CrossRefGoogle Scholar
  10. Schlegelmilch, R. M., & Kramme, R. (2011). Pulmonary function testing. In R. Kramme, K.P. Hoffmann, R.S. Pozos (Eds.), Springer handbook of medical technology (pp. 95–117). Berlin: Springer.CrossRefGoogle Scholar
  11. Sonu, R., & Sharma, K. (2012). Disease detection using analysis of voice parameters. International Journal of Computing Science and Communication Technologies, 4(2), 416–420.Google Scholar
  12. Swanney, M. P., Ruppel, G., Enright, P. L., Pedersen, O. F., Crapo, R. O., Miller, M. R., et al. (2008). Using the lower limit of normal for the FEV1/FVC ratio reduces the misclassification of airway obstruction. Thorax.  https://doi.org/10.1136/thx.2008.098483.Google Scholar
  13. Teixeira, J. P., Oliveira, C., & Lopes, C. (2013). Vocal acoustic analysis—Jitter, shimmer and hnr parameters. Procedia Technology, 9, 1112–1122.CrossRefGoogle Scholar
  14. Vollmer, W. M., Gíslason, Þ, Burney, P., Enright, P. L., Gulsvik, A., Kocabas, A., et al. (2009). Comparison of spirometry criteria for the diagnosis of COPD: Results from the BOLD study. European Respiratory Journal, 34(3), 588–597.CrossRefGoogle Scholar
  15. Wanger, J. (2011). Forced spirometry and related tests. In J. Wanger (Ed.), Pulmonary function testing. Burlington: Jones & Bartlett Publishers.Google Scholar
  16. Yumoto, E., Gould, W. J., & Baer, T. (1982). Harmonics-to-noise ratio as an index of the degree of hoarseness. The Journal of the Acoustical Society of America, 71(6), 1544–1550.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • John Kutor
    • 1
    • 2
    Email author
  • Srinivasan Balapangu
    • 1
  • Jeromy K. Adofo
    • 1
  • Albert Atsu Dellor
    • 1
  • Christopher Nyakpo
    • 1
  • Godfred Akwetey Brown
    • 1
  1. 1.Department of Biomedical EngineeringUniversity of GhanaAccraGhana
  2. 2.School of Engineering Sciences, College of Basic and Applied Sciences (CBAS)University of GhanaAccraGhana

Personalised recommendations