Ambulatory Voice Monitoring

Y. - A. S. Lien, et al., “Voice relative fundamental frequency via neck-skin acceleration in individuals with voice disorders,” Journal of Speech, Language, and Hearing Research, vol. 58, no. 5, pp. 1482-1487, 2015. Publisher's VersionAbstract

Abstract Purpose: This study investigated the use of neck-skin acceleration for relative fundamental frequency (RFF) analysis. Method: Forty individuals with voice disorders associated with vocal hyperfunction and 20 age- and sex-matched control participants were recorded with a subglottal neck-surface accelerometer and a microphone while producing speech stimuli appropriate for RFF. Rater reliabilities, RFF means, and RFF standard deviations derived from the accelerometer were compared with those derived from the microphone. Results: RFF estimated from the accelerometer had slightly higher intrarater reliability and identical interrater reliability compared with values estimated with the microphone. Although sensor type and the Vocal Cycle × Sensor and Vocal Cycle × Sensor × Group interactions showed significant effects on RFF means, the typical RFF pattern could be derived from either sensor. For both sensors, the RFF of individuals with vocal hyperfunction was lower than that of the controls. Sensor type and its interactions did not have significant effects on RFF standard deviations. Conclusions: RFF can be reliably estimated using an accelerometer, but these values cannot be compared with those collected via microphone. Future studies are needed to determine the physiological basis of RFF and examine the effect of sensors on RFF in practical voice assessment and monitoring settings.

D. D. Mehta, J. H. Van Stan, and R. E. Hillman, “Deriving acoustic voice quality measures from subglottal neck-surface acceleration,” Proceedings of the International Conference on Voice Physiology and Biomechanics, 2014. Poster
M. Ghassemi, et al., “Learning to detect vocal hyperfunction from ambulatory neck-surface acceleration features: Initial results for vocal fold nodules,” IEEE Transactions on Biomedical Engineering, vol. 61, no. 6, pp. 1668-1675, 2014. Publisher's VersionAbstract

Voice disorders are medical conditions that often result from vocal abuse/misuse which is referred to generically as vocal hyperfunction. Standard voice assessment approaches cannot accurately determine the actual nature, prevalence, and pathological impact of hyperfunctional vocal behaviors because such behaviors can vary greatly across the course of an individual's typical day and may not be clearly demonstrated during a brief clinical encounter. Thus, it would be clinically valuable to develop noninvasive ambulatory measures that can reliably differentiate vocal hyperfunction from normal patterns of vocal behavior. As an initial step toward this goal we used an accelerometer taped to the neck surface to provide a continuous, noninvasive acceleration signal designed to capture some aspects of vocal behavior related to vocal cord nodules, a common manifestation of vocal hyperfunction. We gathered data from 12 female adult patients diagnosed with vocal fold nodules and 12 control speakers matched for age and occupation. We derived features from weeklong neck-surface acceleration recordings by using distributions of sound pressure level and fundamental frequency over 5-min windows of the acceleration signal and normalized these features so that intersubject comparisons were meaningful. We then used supervised machine learning to show that the two groups exhibit distinct vocal behaviors that can be detected using the acceleration signal. We were able to correctly classify 22 of the 24 subjects, suggesting that in the future measures of the acceleration signal could be used to detect patients with the types of aberrant vocal behaviors that are associated with hyperfunctional voice disorders.

R. E. Hillman, D. Mehta, J. H. Van Stan, M. Zañartu, M. Ghassemi, and J. V. Guttag, “Subglottal ambulatory monitoring of vocal function to improve voice disorder assessment,” The Journal of the Acoustical Society of America, vol. 136, pp. 2260-2260, 2014.
R. E. Hillman, et al., “Future directions in the development of ambulatory monitoring for clinical voice assessment,” Proceedings of the 10th International Conference on Advances in Quantitative Laryngology, Voice and Speech Research, 2013.
D. D. Mehta, M. Zañartu, J. H. Van Stan, S. W. Feng, H. A. Cheyne II, and R. E. Hillman, “Smartphone-based detection of voice disorders by long-term monitoring of neck acceleration features,” Proceedings of the IEEE International Conference on Body Sensor Networks, pp. 1-6, 2013. Paper
M. Zañartu, J. C. Ho, D. D. Mehta, R. E. Hillman, and G. R. Wodicka, “Subglottal impedance-based inverse filtering of voiced sounds using neck surface acceleration,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 21, pp. 1929-1939, 2013.Abstract

A model-based inverse filtering scheme is proposed for an accurate, non-invasive estimation of the aerodynamic source of voiced sounds at the glottis. The approach, referred to as subglottal impedance-based inverse filtering (IBIF), takes as input the signal from a lightweight accelerometer placed on the skin over the extrathoracic trachea and yields estimates of glottal airflow and its time derivative, offering important advantages over traditional methods that deal with the supraglottal vocal tract. The proposed scheme is based on mechano-acoustic impedance representations from a physiologically-based transmission line model and a lumped skin surface representation. A subject-specific calibration protocol is used to account for individual adjustments of subglottal impedance parameters and mechanical properties of the skin. Preliminary results for sustained vowels with various voice qualities show that the subglottal IBIF scheme yields comparable estimates with respect to current aerodynamics-based methods of clinical vocal assessment. A mean absolute error of less than 10% was observed for two glottal airflow measures—maximum flow declination rate and amplitude of the modulation component—that have been associated with the pathophysiology of some common voice disorders caused by faulty and/or abusive patterns of vocal behavior (i.e., vocal hyperfunction). The proposed method further advances the ambulatory assessment of vocal function based on the neck acceleration signal, that previously have been limited to the estimation of phonation duration, loudness, and pitch. Subglottal IBIF is also suitable for other ambulatory applications in speech communication, in which further evaluation is underway.

M. Zañartu, et al., “Toward an objective aerodynamic assessment of vocal hyperfunction using a voice health monitor,” Proceedings of the 8th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, 2013. Paper
M. Ghassemi, et al., “Detecting voice modes for vocal hyperfunction prevention,” Proceedings of the 7th Annual Workshop for Women in Machine Learning. 2012.
D. D. Mehta, et al., “Duration of ambulatory monitoring needed to accurately estimate voice use,” Proceedings of InterSpeech: Annual Conference of the International Speech Communication Association, 2012. Paper Poster
D. D. Mehta, M. Zañartu, S. W. Feng, H. A. Cheyne II, and R. E. Hillman, “Mobile voice health monitoring using a wearable accelerometer sensor and a smartphone platform,” IEEE Transactions on Biomedical Engineering, vol. 59, no. 11, pp. 3090-3096, 2012. Publisher's VersionAbstract

Many common voice disorders are chronic or recurring conditions that are likely to result from faulty and/or abusive patterns of vocal behavior, referred to generically as vocal hyperfunction. An ongoing goal in clinical voice assessment is the development and use of noninvasively derived measures to quantify and track the daily status of vocal hyperfunction so that the diagnosis and treatment of such behaviorally based voice disorders can be improved. This paper reports on the development of a new, versatile, and cost-effective clinical tool for mobile voice monitoring that acquires the high-bandwidth signal from an accelerometer sensor placed on the neck skin above the collarbone. Using a smartphone as the data acquisition platform, the prototype device provides a user-friendly interface for voice use monitoring, daily sensor calibration, and periodic alert capabilities. Pilot data are reported from three vocally normal speakers and three subjects with voice disorders to demonstrate the potential of the device to yield standard measures of fundamental frequency and sound pressure level and model-based glottal airflow properties. The smartphone-based platform enables future clinical studies for the identification of the best set of measures for differentiating between normal and hyperfunctional patterns of voice use.

R. E. Hillman and D. D. Mehta, “Ambulatory monitoring of daily voice use,” Perspectives on Voice and Voice Disorders, vol. 21, no. 2, pp. 56-61, 2011. Publisher's Version Paper