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Related Experiment Video

Updated: Jul 6, 2026

Hemi-laryngeal Setup for Studying Vocal Fold Vibration in Three Dimensions
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Published on: November 25, 2017

Physiological Validation of Glottal Airflow Estimation Using Neck-Surface Accelerometry: A Comparison With

Youjin Kang1, Dahyung Han2, Boram Yun3

  • 1Department of Electronic Engineering, Hanyang University, Seoul, Republic of Korea.

Journal of Voice : Official Journal of the Voice Foundation
|July 4, 2026
PubMed
Summary

Neck-surface accelerometers (ACC) offer a direct measure of vocal fold collision dynamics, outperforming traditional acoustic methods. This finding supports ACC as a key tool for wearable voice assessment and monitoring mechanical load.

Keywords:
ElectroglottographyGlottal airflowNeck-surface accelerometerPhonation typesVoice assessment

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Area of Science:

  • Biomechanics of voice production
  • Wearable sensor technology
  • Speech signal processing

Background:

  • Neck-surface accelerometers (ACC) show potential for ambulatory voice monitoring.
  • ACC signals may capture both aerodynamic and vocal fold collision characteristics.
  • Evaluating ACC's reflection of glottal collision dynamics is crucial.

Purpose of the Study:

  • To investigate how effectively ACC reflects glottal collision dynamics.
  • To compare ACC-derived metrics with electroglottography (EGG) across diverse phonations.
  • To assess ACC's utility beyond simple aerodynamic analysis.

Main Methods:

  • Collected synchronized ACC, microphone (MIC), and EGG signals from nine adults.
  • Analyzed sustained phonations: modal, breathy, falsetto, and creaky.
  • Used inverse filtering to estimate glottal airflow parameters and correlated with EGG contact measures.

Main Results:

  • ACC and MIC signals showed similar trends in Acoustic Quotient (AQ) and Maximum Flow Declination Rate (MFDR).
  • ACC-derived Normalized Amplitude Quotient (NAQ) and H1-H2 showed stronger correlations with EGG contact quotient (r = -0.830, r = -0.848) than MIC.
  • ACC metrics demonstrated higher explanatory power (R^2) for glottal collision dynamics.

Conclusions:

  • ACC faithfully reflects vocal fold collision mechanical energy, providing a direct representation of contact dynamics.
  • ACC offers superior insights into glottal collision compared to conventional acoustic signals.
  • ACC is a foundational tool for biomechanical voice assessment and monitoring mechanical load in daily voice care.