Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Volume velocity in a canine larynx model using time-resolved tomographic particle image velocimetry

  • 57 Accesses

Abstract

In the classic source–filter theory, the source of sound is flow modulation. “Flow” is the flow rate (Q) and flow modulation is dQ/dt. Other investigators have argued, using theoretical, computational, and mechanical models of the larynx, that there are additional sources of sound. To determine the acoustic role of dQ/dt in a tissue model, Q needs to be accurately measured within a few millimeters of the glottal exit; however, no direct measures of Q currently exist. The goal of this study is to obtain this waveform in an excised canine larynx model using time-resolved tomographic particle image velocimetry. The flow rate data are captured simultaneously with acoustic measurements to determine relations with vocal characteristics. The results show that glottal waveform characteristics such as maximum flow declination rate are proportional to the subglottal pressure, fundamental frequency, and acoustic intensity. These findings are important as they use direct measurements of the volume flow at the glottal exit to validate some of the assumptions used in the source–filter theory. In addition, future work will address the accuracy of indirect clinical measurement techniques, such as the Rothenberg mask.

Graphical abstract

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

References

  1. Alipour F, Scherer RC (2002) Pressure and velocity profiles in a static mechanical hemilarynx model. J Acoust Soc Am 112:2996–3003. https://doi.org/10.1121/1.1519540

  2. Anklin M, Drahm W, Rieder A (2006) Coriolis mass flowmeters: overview of the current state of the art and latest research. Flow Meas Instrum. https://doi.org/10.1016/j.flowmeasinst.2006.07.004

  3. Audier P, Sciamarella D, Artana G (2016) Pre-switching bifurcation of a slender jet. Phys Fluids. https://doi.org/10.1063/1.4939711

  4. Barney A, Shadle CH, Davies POAL (1999) Fluid flow in a dynamic mechanical model of the vocal folds and tract. I. Measurements and theory. J Acoust Soc Am 105(1):444–455

  5. Becker S, Kniesburges S, Müller S et al (2009) Flow–structure–acoustic interaction in a human voice model. J Acoust Soc Am. https://doi.org/10.1121/1.3068444

  6. Berke GS, Moore DM, Hantke DR et al (1987) Laryngeal modeling: theoretical, in vitro, in vivo. Laryngoscope. https://doi.org/10.1288/00005537-198707000-00019

  7. Bielamowicz S, Berke GS, Kreiman J, Gerratt BR (1999) Exit jet particle velocity in the in vivo canine laryngeal model with variable nerve stimulation. J Voice. https://doi.org/10.1016/S0892-1997(99)80019-8

  8. Birk V, Kniesburges S, Semmler M et al (2017) Influence of glottal closure on the phonatory process in ex vivo porcine larynges. J Acoust Soc Am doi 10(1121/1):5007952

  9. Cranen B, Boves L (1988) On the measurement of glottal flow. J Acoust Soc Am. https://doi.org/10.1121/1.396658

  10. Cranen B, Schroeter J (1995) Modeling a leaky glottis. J Phon. https://doi.org/10.1016/S0095-4470(95)80040-9

  11. Crighton DG, Dowling AP, Ffowcs-Williams JE et al (1992) Modern methods in analytical acoustics lecture notes. J Acoust Soc Am. https://doi.org/10.1121/1.404334

  12. Drechsel JS, Thomson SL (2008) Influence of supraglottal structures on the glottal jet exiting a two-layer synthetic, self-oscillating vocal fold model. J Acoust Soc Am. https://doi.org/10.1121/1.2897040

  13. Elsinga GE, Van Oudheusden BW, Scarano F (2006) Experimental assessment of tomographic-PIV accuracy. In: 13th international symposium on applications of laser techniques to fluid mechanics, Lisbon, Portugal, paper, vol 20

  14. Fant G (1981) The source filter concept in voice production. STL-QPSR 1:21–37

  15. Farbos de Luzan C, Chen J, Mihaescu M et al (2015) Computational study of false vocal folds effects on unsteady airflows through static models of the human larynx. J Biomech 48:1248–1257

  16. Fulcher L, Lodermeyer A, Kähler G et al (2019) Geometry of the vocal tract and properties of phonation near threshold: calculations and measurements. Appl Sci. https://doi.org/10.3390/app9132755

  17. Hirschberg A (1992) Some fluid dynamic aspects of speech. Bull Commun Parlée 2:7–30

  18. Ho CM, Gutmark E (1987) Vortex induction and mass entrainment in a small-aspect-ratio elliptic jet. J Fluid Mech. https://doi.org/10.1017/S0022112087001587

  19. Holmberg EB, Hillman RE, Perkell JS (1989) Glottal airflow and transglottal air pressure measurements for male and female speakers in low, normal, and high pitch. J Voice. https://doi.org/10.1016/S0892-1997(89)80051-7

  20. Howe MS, McGowan RS (2010) On the single-mass model of the vocal folds. Fluid Dyn Res. https://doi.org/10.1088/0169-5983/42/1/015001

  21. Howe MS, McGowan RS (2011) Production of sound by unsteady throttling of flow into a resonant cavity, with application to voiced speech. J Fluid Mech. https://doi.org/10.1017/S0022112010006117

  22. Kataoka H, Arii S, Ochiai Y et al (2007) Analysis of human glottal velocity using hot-wire anemometry and high-speed imaging. Ann Otol Rhinol Laryngol. https://doi.org/10.1177/000348940711600505

  23. Khosla S, Murugappan S, Lakhamraju R, Gutmark E (2008) Using particle imaging velocimetry to measure anterior–posterior velocity gradients in the excised canine larynx model. Ann Otol Rhinol Laryngol. https://doi.org/10.1177/000348940811700212

  24. Khosla S, Oren L, Ying J, Gutmark E (2014) Direct simultaneous measurement of intraglottal geometry and velocity fields in excised larynges. Laryngoscope. https://doi.org/10.1002/lary.24512

  25. Kniesburges S, Becker S, Mueller S, Delgado A, Link G, Kaltenbacher M, Doellinger M (2008) Experimental study of the fluid-structure-acoustic interaction in a human voice model. J Acoust Soc Am 123(5):3737–3737

  26. Krebs F, Silva F, Sciamarella D, Artana G (2012) A three-dimensional study of the glottal jet. Exp Fluids. https://doi.org/10.1007/s00348-011-1247-3

  27. Lehto L, Airas M, Björkner E et al (2007) Comparison of two inverse filtering methods in parameterization of the glottal closing phase characteristics in different phonation types. J Voice. https://doi.org/10.1016/j.jvoice.2005.10.007

  28. Lodermeyer A, Becker S, Döllinger M, Kniesburges S (2015) Phase-locked flow field analysis in a synthetic human larynx model. Exp Fluids. https://doi.org/10.1007/s00348-015-1942-6

  29. Lodermeyer A, Tautz M, Becker S et al (2018) Aeroacoustic analysis of the human phonation process based on a hybrid acoustic PIV approach. Exp Fluids. https://doi.org/10.1007/s00348-017-2469-9

  30. Lucero JC, Lourenço KG, Hermant N et al (2012) Effect of source–tract acoustical coupling on the oscillation onset of the vocal folds. J Acoust Soc Am. https://doi.org/10.1121/1.4728170

  31. Luo H, Mittal R, Zheng X et al (2008) An immersed-boundary method for flow–structure interaction in biological systems with application to phonation. J Comput Phys. https://doi.org/10.1016/j.jcp.2008.05.001

  32. McGowan RS (1988) An aeroacoustic approach to phonation. J Acoust Soc Am 83(2):696–704

  33. McPhail MJ, Campo ET, Krane MH (2019) Aeroacoustic source characterization in a physical model of phonation. J Acoust Soc Am. https://doi.org/10.1121/1.5122787

  34. Mehta RD (1985) Turbulent boundary layer perturbed by a screen. AIAA J 23:1335–1342

  35. Monsen RB, Engebretson AM (1977) Study of variations in the male and female glottal wave. J Acoust Soc Am. https://doi.org/10.1121/1.381593

  36. Morel T (1975) Comprehensive design of axisymmetric wind tunnel contractions. J Fluids Eng 97:225. https://doi.org/10.1115/1.3447255

  37. Mylavarapu G, Murugappan S, Mihaescu M et al (2009) Validation of computational fluid dynamics methodology used for human upper airway flow simulations. J Biomech 42:1553–1559

  38. Neubauer J, Zhang Z, Miraghaie R, Berry DA (2007) Coherent structures of the near field flow in a self-oscillating physical model of the vocal folds. J Acoust Soc Am doi 10(1121/1):2409488

  39. Nielson JR, Daily DJ, Truscott TT et al (2013) Simultaneous tracking of vocal fold superior surface motion and glottal jet dynamics. https://doi.org/10.1115/IMECE2013-64574

  40. Oren L, Khosla S, Gutmark E (2014) Intraglottal geometry and velocity measurements in canine larynges. J Acoust Soc Am 135:380–388. https://doi.org/10.1121/1.4837222

  41. Oren L, Gutmark E, Khosla S (2015a) Intraglottal velocity and pressure measurements in a hemilarynx model. J Acoust Soc Am 137:935–943. https://doi.org/10.1121/1.4906833

  42. Oren L, Khosla S, Dembinski D et al (2015b) Direct measurement of planar flow rate in an excised canine larynx model. Laryngoscope 125:383–388

  43. Oren L, Khosla S, Gutmark E (2019) Medial surface dynamics as a function of subglottal pressure in a canine larynx model. J Voice. https://doi.org/10.1016/j.jvoice.2019.07.015

  44. Pickett TM (1956) Effects of vocal force on the intelligibility of speech sounds. J Acoust Soc Am. https://doi.org/10.1121/1.1908510

  45. Rothenberg M (1973) A new inverse-filtering technique for deriving the glottal air flow waveform during voicing. J Acoust Soc Am. https://doi.org/10.1121/1.1975066

  46. Stevens KN (2000) Acoust Phon 30:55–127

  47. Sulter AM, Wit HP (1996) Glottal volume velocity waveform characteristics in subjects with and without vocal training, related to gender, sound intensity, fundamental frequency, and age. J Acoust Soc Am 100:3360–3373. https://doi.org/10.1121/1.416977

  48. Sundberg J (1987) The science of the singing voice. University Press, Dekalb

  49. Taylor CJ, Tarbox GJ, Bolster BD et al (2019) Magnetic resonance imaging-based measurement of internal deformation of vibrating vocal fold models. J Acoust Soc Am. https://doi.org/10.1121/1.5091009

  50. Titze IR (1988) The physics of small-amplitude oscillation of the vocal folds. J Acoust Soc Am 83:1536–1552

  51. Titze IR (2006) Theoretical analysis of maximum flow declination rate versus maximum area declination rate in phonation. J Speech Lang Hear Res 49:439–447. https://doi.org/10.1044/1092-4388(2006/034)

  52. Titze IR (2008) Nonlinear source–filter coupling in phonation: theory. J Acoust Soc Am. https://doi.org/10.1121/1.2832337

  53. Titze IR, Martin DW (1998) Principles of voice production. J Acoust Soc Am 104:1148. https://doi.org/10.1121/1.424266

  54. Triep M, Brücker C (2010a) Three-dimensional nature of the glottal jet. J Acoust Soc Am. https://doi.org/10.1121/1.3299202

  55. Triep M, Brücker C (2010b) Three-dimensional nature of the glottal jet. J Acoust Soc Am 127:1537–1547

  56. Triep M, Brücker C, Schröder W (2005) High-speed PIV measurements of the flow downstream of a dynamic mechanical model of the human vocal folds. Exp Fluids 39(2):232–245

  57. Verneuil A, Gerratt BR, Berry DA et al (2003) Modeling measured glottal volume velocity waveforms. Ann Otol Rhinol Laryngol. https://doi.org/10.1177/000348940311200204

  58. Westerweel J, Scarano F (2005) Universal outlier detection for PIV data. Exp Fluids. https://doi.org/10.1007/s00348-005-0016-6

  59. Zhang Z, Neubauer J, Berry DA (2006) The influence of subglottal acoustics on laboratory models of phonation. J Acoust Soc Am. https://doi.org/10.1121/1.2225682

  60. Zheng X, Bielamowicz S, Luo H, Mittal R (2009) A computational study of the effect of false vocal folds on glottal flow and vocal fold vibration during phonation. Ann Biomed Eng 37:625–642. https://doi.org/10.1007/s10439-008-9630-9

Download references

Acknowledgements

This project was supported by NIH Grant no. R01 DC009435 from the National Institute of Deafness and Other Communication Disorders.

Author information

Correspondence to Charles Farbos de Luzan.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Farbos de Luzan, C., Oren, L., Maddox, A. et al. Volume velocity in a canine larynx model using time-resolved tomographic particle image velocimetry. Exp Fluids 61, 63 (2020). https://doi.org/10.1007/s00348-020-2896-x

Download citation