Voice disorders affect approximately 6.6% of the working-age population in the United States. 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. Such behaviorally based disorders can be difficult to accurately assess in the clinical setting and could potentially be much better characterized by long-term ambulatory monitoring of vocal function as individuals engage in their typical daily activities. Devices that use a neck-placed miniature accelerometer (ACC) as a phonation sensor have shown the best potential for unobtrusive long-term monitoring of vocal function. The adoption, however, of this technology into clinical practice has been quite limited because of: 1) technical limitations of current devices, measures, and analysis algorithms;2) the relatively high cost of commercially-available systems;and 3) the lack of statistically robust studies to determine the true diagnostic capabilities of ACC-based measures. The overall goal of the proposed project (in response to PAR-09-057) is to develop ACC-based ambulatory monitoring of vocal function into a valid, reliable, and cost-effective clinical tool that can be used to accurately identify and differentiate patterns of voice use that are associated with hyperfunctional voice disorders. Achieving this goal will: 1) greatly improve clinical assessment of these commonly-occurring types of voice disorders, 2) enable voice therapy to more accurately target specific hyperfunctional behaviors for individual patients, and 3) provide the basis for future efforts to develop ambulatory biofeedback approaches that have the potential to facilitate more efficient and effective behavioral treatment of these disorders. In the R21 phase of this project we will develop and validate a new, versatile, and cost-effective system for ambulatory voice monitoring that uses a neck-placed miniature ACC as the phonation sensor and a mobile personal digital device (e.g., a smartphone) as the data acquisition platform. An effort will be made to facilitate the continued availability of this technology for clinical use and development by designing system software and basic interface circuitry that is largely compatible with new generations of personal digital device architecture. The R33 phase of the project will focus on using the new ambulatory monitoring system to collect data from a large, statistically robust sample of patients with hyperfunctional voice disorders (before and after treatment) and matched controls. These data will be subjected to three types of analysis approaches in an effort to identify the best set of measures for differentiating among hyperfunctional and normal patterns of vocal behavior: 1) previously-developed ambulatory measures of vocal function that include vocal dosage;2) measures based on estimates of glottal airflow that are extracted from the ACC signal using a new vocal system model, and 3) measures based on methods that have been used successfully in analyzing long-term recordings of other physiologic signals (e.g., electrocardiograms) for risk stratification of patients.
The current proposal seeks to address the main goal set forth in Program Announcement PAR-09-057 from the National Institute on Deafness and Other Communication Disorders (NIDCD), which is ...to develop new or enhanced diagnostic, intervention and treatment paradigms with potential for widespread, cost-effective application in the NIDCD mission areas..., which include voice and speech. This goal will be accomplished in the current project by developing ambulatory voice monitoring into a valid, reliable, and cost-effective clinical tool that can be used to improve the diagnosis and treatment of voice disorders.
|Mehta, Daryush D; Van Stan, Jarrad H; Hillman, Robert E (2016) Relationships between vocal function measures derived from an acoustic microphone and a subglottal neck-surface accelerometer. IEEE/ACM Trans Audio Speech Lang Process 24:659-668|
|Lien, Yu-An S; Calabrese, Carolyn R; Michener, Carolyn M et al. (2015) Voice Relative Fundamental Frequency Via Neck-Skin Acceleration in Individuals With Voice Disorders. J Speech Lang Hear Res 58:1482-7|
|Van Stan, Jarrad H; Mehta, Daryush D; Zeitels, Steven M et al. (2015) Average Ambulatory Measures of Sound Pressure Level, Fundamental Frequency, and Vocal Dose Do Not Differ Between Adult Females With Phonotraumatic Lesions and Matched Control Subjects. Ann Otol Rhinol Laryngol 124:864-74|
|Van Stan, Jarrad H; Mehta, Daryush D; Hillman, Robert E (2015) The Effect of Voice Ambulatory Biofeedback on the Daily Performance and Retention of a Modified Vocal Motor Behavior in Participants With Normal Voices. J Speech Lang Hear Res 58:713-21|
|Mehta, Daryush D; Wolfe, Patrick J (2015) Statistical properties of linear prediction analysis underlying the challenge of formant bandwidth estimation. J Acoust Soc Am 137:944-50|
|Llico, AndrÃ©s F; ZaÃ±artu, MatÃas; GonzÃ¡lez, AgustÃn J et al. (2015) Real-time estimation of aerodynamic features for ambulatory voice biofeedback. J Acoust Soc Am 138:EL14-9|
|ZaÃ±artu, MatÃas; Galindo, Gabriel E; Erath, Byron D et al. (2014) Modeling the effects of a posterior glottal opening on vocal fold dynamics with implications for vocal hyperfunction. J Acoust Soc Am 136:3262|
|Ghassemi, Marzyeh; Van Stan, Jarrad H; Mehta, Daryush D et al. (2014) Learning to detect vocal hyperfunction from ambulatory neck-surface acceleration features: initial results for vocal fold nodules. IEEE Trans Biomed Eng 61:1668-75|
|ZaÃ±artu, MatÃas; Ho, Julio C; Mehta, Daryush D et al. (2013) Subglottal Impedance-Based Inverse Filtering of Voiced Sounds Using Neck Surface Acceleration. IEEE Trans Audio Speech Lang Process 21:1929-1939|
|Mehta, Daryush D; Zanartu, Matias; Feng, Shengran W et al. (2012) Mobile voice health monitoring using a wearable accelerometer sensor and a smartphone platform. IEEE Trans Biomed Eng 59:3090-6|
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