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Semi-Automated Analysis of Peak Amplitude and Latency for Auditory Brainstem Response Waveforms Using R

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Normalized time-domain parameters for electroglottographic waveforms.

Sten Ternström¹

¹Department of Speech, Music and Hearing, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Swedenstern@kth.se.

The Journal of the Acoustical Society of America

|August 3, 2019

Summary

This study introduces new methods for analyzing electroglottography (EGG) waveforms, improving vocal fold characterization without arbitrary thresholds. The approach offers a more reliable way to assess phonation and vocal fold contact. Keywords: electroglottography, phonation, vocal fold analysis.

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Area of Science:

Speech Science
Bioacoustics
Medical Instrumentation

Background:

Electroglottography (EGG) is crucial for non-invasive phonation analysis.
Current EGG parameterizations yield inconsistent results due to arbitrary thresholds and event detection.
A need exists for robust and reproducible EGG analysis methods.

Purpose of the Study:

To develop novel parameterizations for the electroglottographic waveform.
To eliminate reliance on arbitrary thresholds and contacting events in EGG analysis.
To improve the characterization of vocal fold contacting.

Main Methods:

Developed signal preconditioning schemes for EGG data.
Implemented time-domain period detection algorithms.
Formulated a normalized contact quotient and normalized peak derivative without thresholds.
Created a heuristic combination of parameters to resolve contact quotient ambiguity.

Main Results:

The new methods successfully characterize phonation without arbitrary thresholds or contacting events.
A normalized contact quotient and normalized peak derivative were formulated.
The combined parameter approach disambiguates moderate contact quotient values, distinguishing firm from weak/absent vocal fold contact.
Preconditioning and period detection schemes show minor improvements over existing methods.

Conclusions:

A threshold-independent approach to EGG analysis is feasible and effective.
The proposed methods provide a more reliable and unambiguous characterization of vocal fold dynamics.
The algorithms are computationally simple and fast, suitable for clinical application.