Dependencies and Ill-designed Parameters Within High-speed Videoendoscopy and Acoustic Signal Analysis

J Voice. 2019 Sep;33(5):811.e1-811.e12. doi: 10.1016/j.jvoice.2018.04.011. Epub 2018 May 31.

Abstract

Objective: The phonatory process is often judged during sustained phonation by analyzing the acoustic voice signal and the vocal fold vibrations. Many formulas and parameters have been suggested for qualifying the characteristics of the acoustic signal and the vocal fold vibrations during sustained phonation. These parameters are directly computed from the acoustic signal and the endoscopic glottal area waveform (GAW). The GAW is calculated from laryngeal high-speed videoendoscopy (HSV) recordings and describes the increase and decrease of the glottal area during the phonation process, that is, the opening and closing of the two oscillating vocal folds over time. However, some of the parameters have strong mathematical dependencies with one another and some are ill-defined. The purpose of this study is to identify mathematical dependencies between parameters with the aim of reducing their numbers and suggesting which parameters may best describe the properties of the GAW and the acoustical signal.

Methods: In this preliminary investigation, 20 frequently used parameters are examined: 10 GAW only and 10 both GAW and acoustic parameters.

Results: In total 13 parameters can be neglected because of mathematical dependencies. In addition, nine of these parameters show problematic features that range from unexpected behavior to ill definition.

Conclusions: Reducing the number of parameters appears to be necessary to standardize vocal fold function analysis. This may lead to better comparability of research results from different studies.

Keywords: Glottal area waveform; High speed video endoscopy; Ill design; Mathematical dependencies; Parameters.

MeSH terms

  • Acoustics*
  • Glottis / diagnostic imaging*
  • Glottis / physiology
  • Humans
  • Laryngoscopy*
  • Models, Theoretical*
  • Phonation*
  • Predictive Value of Tests
  • Signal Processing, Computer-Assisted*
  • Time Factors
  • Vibration
  • Video Recording*
  • Voice Quality*