Publication:
Using Ambulatory Voice Monitoring to Investigate Common Voice Disorders: Research Update

Thumbnail Image

Open/View Files

Date

2015

Published Version

Journal Title

Journal ISSN

Volume Title

Publisher

Frontiers Media S.A.
The Harvard community has made this article openly available. Please share how this access benefits you.

Research Projects

Organizational Units

Journal Issue

Citation

Mehta, Daryush D., Jarrad H. Van Stan, Matías Zañartu, Marzyeh Ghassemi, John V. Guttag, Víctor M. Espinoza, Juan P. Cortés, Harold A. Cheyne, and Robert E. Hillman. 2015. “Using Ambulatory Voice Monitoring to Investigate Common Voice Disorders: Research Update.” Frontiers in Bioengineering and Biotechnology 3 (1): 155. doi:10.3389/fbioe.2015.00155. http://dx.doi.org/10.3389/fbioe.2015.00155.

Research Data

Abstract

Many common voice disorders are chronic or recurring conditions that are likely to result from inefficient and/or abusive patterns of vocal behavior, referred to as vocal hyperfunction. The clinical management of hyperfunctional voice disorders would be greatly enhanced by the ability to monitor and quantify detrimental vocal behaviors during an individual’s activities of daily life. This paper provides an update on ongoing work that uses a miniature accelerometer on the neck surface below the larynx to collect a large set of ambulatory data on patients with hyperfunctional voice disorders (before and after treatment) and matched-control subjects. Three types of analysis approaches are being employed in an effort to identify the best set of measures for differentiating among hyperfunctional and normal patterns of vocal behavior: (1) ambulatory measures of voice use that include vocal dose and voice quality correlates, (2) aerodynamic measures based on glottal airflow estimates extracted from the accelerometer signal using subject-specific vocal system models, and (3) classification based on machine learning and pattern recognition approaches that have been used successfully in analyzing long-term recordings of other physiological signals. Preliminary results demonstrate the potential for ambulatory voice monitoring to improve the diagnosis and treatment of common hyperfunctional voice disorders.

Description

Keywords

voice monitoring, accelerometer, vocal function, voice disorders, vocal hyperfunction, glottal inverse filtering, machine learning

Terms of Use

This article is made available under the terms and conditions applicable to Other Posted Material (LAA), as set forth at Terms of Service

Endorsement

Review

Supplemented By

Referenced By

Related Stories