Project Summary/Abstract:
Approximately 13 million Americans suffer from age-related dysphonia, a communication disorder resulting
in hoarseness and weak voice. Communication difficulty places older adults at increased risk for mental and
physical health problems, and dysphonia specifically interferes with the ability to participate in the work force
and to be heard and understood when speaking in noisy environments and over the phone. Despite the
importance of successful treatment of age-related dysphonia, voice therapy and surgery improve voice for a
just small fraction of patients. A key barrier to improving treatment algorithms in age-related dysphonia is lack
of knowledge about how voice therapy techniques change voice and which factors moderate that
improvement. The objectives for this application are to determine the mechanisms by which specific therapy
tasks improve voice in age-related dysphonia, and the conditions that limit the extent of improvement. The
aims are directed at understanding the physics of voice therapies, aspects that can be studied with
physiological data collected from voice users combined with theoretical and computational models. The
Specific Aims are: (1) To determine how therapy tasks that modify respiration, vocal function, and vocal tract
shape alter vocal fold vibration in older adults with age-related dysphonia, and (2) To determine through
computational modeling how modifications to respiratory and vocal tract parameters alter glottal flow, the
acoustic signal, and voice quality.
In Aim 1, we will use laryngeal high-speed videoendoscopy to measure the changes to vocal fold
kinematics as participants complete several voice therapy tasks. In Aim 2, we will personalize a computational
vocal tract model to a subset of participants from Aim 1 in order to simulate incremental changes to individual
airflow and vocal tract parameters and combinations of the parameters. Results will be analyzed using
aerodynamic, acoustic, and perceptual measures. Taken together, the studies will provide the information
necessary to determine the mechanisms by which specific tasks improve vocal function and voice quality. The
results will be used to generate a matrix showing the extent of improvement to vocal fold vibration, acoustic
measures, and voice quality with each therapy task or combination of tasks for a given severity level. The
matrix will provide guidance for therapy planning based on initial patient presentation and will provide direction
for novel therapies in the future. The resulting algorithm will be tested using human subjects in future work.