Vocal fold vibratory characteristics of healthy geriatric females--analysis of high-speed digital images

J Voice. 2012 Nov;26(6):751-9. doi: 10.1016/j.jvoice.2011.12.002. Epub 2012 May 26.

Abstract

Objectives/hypothesis: A high proportion of the geriatric population suffers from presbylaryngis and presbyphonia; however, our knowledge of vibratory patterns in this population is almost nonexistent. In this study, we investigate the vocal fold vibratory patterns of healthy elderly females to determine which features or combination of them could best describe the geriatric voices.

Study design: Cross-sectional study with 20 elderly healthy females with no history of voice problems.

Methods: Hilbert transformed glottal area waveforms (GAWs) from serial high-speed digital imaging of sustained phonation are used to provide quantitative measures of glottal vibratory characteristics and perturbations; open quotient, jitter, and shimmer. Nyquist plots provide interpretable patterns to portray the vibratory characteristics as clear, pressed, breathy, and atypical patterns.

Results: The GAW from most elderly speakers (50%) showed vibratory characteristics associated with a more pressed voice and higher glottal perturbation values: their Nyquist plot patterns show wide scatterings around the rim of the plot reflecting a much-reduced ability in sustaining vibratory oscillation; these were distinct differences from previously reported data on younger speakers. Qualitative examination revealed more anteriorly placed glottal gaps in the geriatric females.

Conclusion: These findings have important implications in understanding voice production in the geriatric population and in helping to establish normal perturbation references among female speakers across age.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • Aging
  • Biomechanical Phenomena
  • Cross-Sectional Studies
  • Female
  • Fourier Analysis
  • Humans
  • Laryngoscopy / methods*
  • Middle Aged
  • Pattern Recognition, Automated
  • Phonation*
  • Reproducibility of Results
  • Signal Processing, Computer-Assisted*
  • Time Factors
  • Vibration
  • Vocal Cords / physiology*
  • Voice Quality*