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Daryush Mehta, Ph.D.

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I continue research efforts into the clinical analysis of normal and disordered voice production with particular emphasis on advanced statistical signal processing algorithms and ambulatory monitoring of daily voice use. My work bridges the areas of statistical signal processing and clinical voice assessment.

I investigate the details of the relationship between the motion of the vocal folds (the "voice box") and the acoustics of voice production. My expertise is in signal processing and acoustic voice analysis, and I bring these engineering tools to clinical voice research. We have developed a comprehensive laryngeal high-speed videoendoscopy system to image and quantify vocal fold vibratory characteristics and relate them to voice-related sensor measurements and mathematical models. Other major efforts develop a smartphone platform for tracking voice use using an accelerometer taped to the neck.

We hope that our results will aid voice surgeons and speech-language pathologists in better understanding the mechanisms of normal and disordered voice production.

The research activities and funding listed below are automatically derived from NIH ExPORTER and other sources, which might result in incorrect or missing items. Faculty can login to make corrections and additions.
  1. R01DC019083 (MEHTA, DARYUSH DINYAR) Sep 1, 2021 - May 31, 2026
    Ambulatory monitoring of a vocal efficiency index to improve the clinical management of voice disorders
    Role: Principal Investigator
  2. R21DC015877 (MEHTA, DARYUSH DINYAR) Jan 6, 2017 - Apr 30, 2020
    Non-invasive estimation of subglottal pressure during natural speech to improve clinical voice assessment
    Role: Principal Investigator

Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
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Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.