This Phase I SBIR will develop a new clinical software that can be used by Speech Language Pathologists (SLPs)
to inform the assessment and treatment of Muscle Tension Dysphonia (MTD), one of the most common voice
disorders in clinical practice. MTD is characterized by abnormal coactivation of muscles in and around the larynx
that causes vocal strain - leading to discomfort and pain that impede vocal communication and may lead to
surgery. While voice therapy can mitigate these health risks by reducing laryngeal tension and restoring muscle
balance, the current standard for guiding therapy is by manual palpations and auditory-perceptual impressions
– highly subjective methods with poor inter-rater reliability. The most direct approach to quantitative measures
of laryngeal muscle tension is manual analysis of vocal fold images from an endoscopy – an invasive and time-
consuming method that is not clinically viable for routine assessment and management of MTD. These methods
are also incompatible with the recent need for technology that facilitates remote assessment in the wake of
COVID-19. We will address these needs by developing a new non-contact software tool that provides accurate,
valid, acoustic measures of MTD during speech exercises involving the offset and onset of vocalization. This
approach has been shown in our prior NIH-funded studies to elicit measurable acoustic changes associated with
the presence and absence of MTD and following voice therapy. Leveraging this clinical foundation, our team of
signal processing experts at Altec Inc. will partner with speech researchers, SLPs and otolaryngologists at Boston
University to translate our preliminary laboratory-based software into a turn-key clinical tool to support both
in-person and remote assessment and management of MTD. We will do so by translating our existing time-
consuming manual approach for measuring laryngeal tension into clinical software that uses fully-automated
algorithms to achieve high accuracy when tested on an existing database of N=450 individuals with and without
MTD (Aim 1). The automated algorithms will be complemented by software to guide patient compliance with
the MTD-specific speech exercises and provide SLPs with quantitative outcome measures for a robust, clinically-
viable implementation (Aim 2). Aim 3 will evaluate our MTD software prototype by N=4 SLPs in N=12 patients
with MTD to demonstrate the proof of concept that: 1) it provides accurate measures compared to validated
manual procedures; 2) it detects changes in laryngeal tension due to increased vocal effort or laryngeal massage
therapy with >95% agreement to manual procedures; and 3) it achieves favorable ratings of feasibility,
acceptability and perceived value by patients and SLPs. Phase II will advance our Phase I prototype with real-
time calculations, an acoustic signal quality monitor, and a HIPPA-compliant data management infrastructure
for clinical point-of-care or remote use. It’s reliance on low-cost, readily available, non-contact sensing provides
a practical and effective tool to support in-person and remote clinical care for those with MTD that advances the
NIDCD priorities for technologies to improve health among individuals with speech and language disorders.
1