Literature DB >> 15907431

Analysis of vocal-fold vibrations from high-speed laryngeal images using a Hilbert transform-based methodology.

Yuling Yan1, Kartini Ahmad, Melda Kunduk, Diane Bless.   

Abstract

This paper presents a Hilbert transform-based approach to analyze vocal fold vibrations in human subjects exhibiting normal and abnormal voice productions. This new approach is applied to the analysis of glottal area waveform (GAW) and is capable of providing useful information on the vocal fold vibration. The GAW is extracted from high-speed laryngeal images by delineating the glottal edge for each image frame. An analytic signal is generated through the Hilbert transform of the GAW, which yields a recognizable pattern of the vocal fold vibration in the analytic phase plane. The vibratory pattern is comprehensive and can be correlated with specific voice conditions. Quantitative measures of the glottal perturbation are introduced using the analytic amplitude and instantaneous frequency obtained from the analysis. Examples of clinical voice recordings are used to evaluate and test the effectiveness of this approach in providing qualitative representation and quantitative characteristics of vocal fold vibratory behavior. The results demonstrate the potential of using this new analytical tool incorporated with the high-speed laryngeal imaging modality for clinical voice assessment.

Entities:  

Mesh:

Year:  2005        PMID: 15907431     DOI: 10.1016/j.jvoice.2004.04.006

Source DB:  PubMed          Journal:  J Voice        ISSN: 0892-1997            Impact factor:   2.009


  14 in total

1.  Efficient and effective extraction of vocal fold vibratory patterns from high-speed digital imaging.

Authors:  Yu Zhang; Erik Bieging; Henry Tsui; Jack J Jiang
Journal:  J Voice       Date:  2008-05-27       Impact factor: 2.009

Review 2.  Advances in laryngeal imaging.

Authors:  Antanas Verikas; Virgilijus Uloza; Marija Bacauskiene; Adas Gelzinis; Edgaras Kelertas
Journal:  Eur Arch Otorhinolaryngol       Date:  2009-07-19       Impact factor: 2.503

3.  Laryngeal High-Speed Videoendoscopy: Rationale and Recommendation for Accurate and Consistent Terminology.

Authors:  Dimitar D Deliyski; Robert E Hillman; Daryush D Mehta
Journal:  J Speech Lang Hear Res       Date:  2015-10       Impact factor: 2.297

4.  Kinematic measurements of the vocal-fold displacement waveform in typical children and adult populations: quantification of high-speed endoscopic videos.

Authors:  Rita Patel; Kevin D Donohue; Harikrishnan Unnikrishnan; Richard J Kryscio
Journal:  J Speech Lang Hear Res       Date:  2015-04       Impact factor: 2.297

5.  Biomechanical modeling of the three-dimensional aspects of human vocal fold dynamics.

Authors:  Anxiong Yang; Jörg Lohscheller; David A Berry; Stefan Becker; Ulrich Eysholdt; Daniel Voigt; Michael Döllinger
Journal:  J Acoust Soc Am       Date:  2010-02       Impact factor: 1.840

6.  Voice pathology classification based on High-Speed Videoendoscopy.

Authors:  D Panek; A Skalski; T Zielinski; D D Deliyski
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2015-08

7.  The glottaltopogram: a method of analyzing high-speed images of the vocal folds.

Authors:  Gang Chen; Jody Kreiman; Abeer Alwan
Journal:  Comput Speech Lang       Date:  2014-09-01       Impact factor: 1.899

8.  An automatic method to quantify mucosal waves via videokymography.

Authors:  Jack J Jiang; Yu Zhang; Michael P Kelly; Erik T Bieging; Matthew R Hoffman
Journal:  Laryngoscope       Date:  2008-08       Impact factor: 3.325

9.  Fully automatic segmentation of glottis and vocal folds in endoscopic laryngeal high-speed videos using a deep Convolutional LSTM Network.

Authors:  Mona Kirstin Fehling; Fabian Grosch; Maria Elke Schuster; Bernhard Schick; Jörg Lohscheller
Journal:  PLoS One       Date:  2020-02-10       Impact factor: 3.240

10.  Measurement of glottal cycle characteristics between children and adults: physiological variations.

Authors:  Rita R Patel; Denis Dubrovskiy; Michael Döllinger
Journal:  J Voice       Date:  2014-03-12       Impact factor: 2.009

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