# Functional synergistic perilaryngeal muscle network using synchronized multi-sensor surface electromyography to improve diagnosis and treatment of voice disorders > **NIH NIH R01** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2024 · $687,872 ## Abstract Project Summary/Abstract There is a significant gap in understanding and quantifying vocal hyperfunction, a common symptom in patients with phonotraumatic and nonphonotraumatic dysphonia. Vocal hyperfunction is characterized by excessive per- ilaryngeal muscle activity and often leads to muscle pain, increased vocal effort and strain, and vocal fatigue. Current diagnostic methods rely heavily on subjective patient reports and unvalidated clinical evaluations, mak- ing it challenging for clinicians to accurately diagnose and track treatment outcomes, which ultimately impacts the quality of care provided to these patients. The proposed research aims to address this gap by developing a novel biomarker of vocal hyperfunction: functional synergistic perilaryngeal muscle network connectivity using synchronized multisensor surface electromyography. This innovative approach will create a new spectrotempo- ral synergistic scan to quantify the complex coordination (and discoordination) of perilaryngeal muscles during typical and dysphonic voicing. This method is expected to provide a more reliable and objective measure of vo- cal hyperfunction. The central hypothesis is that vocal hyperfunction is characterized by disturbances in mus- cle coordination during voicing, which can be measured using the functional synergistic perilaryngeal muscle network connectivity scans. This hypothesis will be tested in three aims. Aim 1: Distinguish patterns of peri- laryngeal muscle discoordination across dysphonic conditions. Aim 2: Quantify the synergistic perilaryngeal neuromuscular response to standard treatment. Aim 3: Determine the synergistic perilaryngeal neuromuscular response to vocal demand. These specific aims will improve understanding of the variable pathophysiology of vocal hyperfunction in different types of dysphonia. The proposed research is significant because it will shift our understanding of voice disorders by providing an objective biomarker of vocal hyperfunction pathophysiology. This approach, characterized by its objectivity, reliability, repeatability, and specificity, is crucial for accurate di- agnosis. This will, in turn, enhance the delivery of effective care, promote early diagnosis, reduce instances of misdiagnosis, and contribute to the advancement towards precision medicine. Objective measurement of vo- cal hyperfunction can also help navigate treatment plans by tracking neurophysiological responses, enabling informed therapy and dosing. Ultimately, the knowledge gained from this research has the potential to inform future clinical trials assessing the predictive ability of this biomarker for treatment responses for vocal hyperfunc- tion. This could lead to a paradigm shift in the management of vocal hyperfunction-related dysphonia, paving the way for more targeted and effective treatments ## Key facts - **NIH application ID:** 10981342 - **Project number:** 1R01DC021452-01A1 - **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE - **Principal Investigator:** Aaron Matthew Johnson - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $687,872 - **Award type:** 1 - **Project period:** 2024-07-05 → 2029-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10981342 ## Citation > US National Institutes of Health, RePORTER application 10981342, Functional synergistic perilaryngeal muscle network using synchronized multi-sensor surface electromyography to improve diagnosis and treatment of voice disorders (1R01DC021452-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10981342. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*