Smartphone-based detection of voice disorders by long-term monitoring of neck acceleration features

Abstract

Many common voice disorders are chronic or recurring conditions that are likely to result from inefficient and/or abusive patterns of vocal behavior, termed vocal hyperfunction. Thus an ongoing goal in clinical voice assessment is the long-term monitoring of noninvasively derived measures to track hyperfunction. This paper reports on a smartphone-based voice health monitor that records the high-bandwidth accelerometer signal from the neck skin above the collarbone. Data collection is under way from patients with vocal hyperfunction and matched-control subjects to create a dataset designed to identify the best set of diagnostic measures for hyperfunctional patterns of vocal behavior. Vocal status is tracked from neck acceleration using previously-developed vocal dose measures and novel model-based features of glottal airflow estimates. Clinically, the treatment of hyperfunctional disorders would be greatly enhanced by the ability to unobtrusively monitor and quantify detrimental behaviors and, ultimately, to provide real-time biofeedback that could facilitate healthier voice use.