Research work

In our interdisciplinary department, we are developing new methods in clinical research that will enable objective voice diagnostics in the future. Of particular impotance is the quantitative analysis of endoscopic high-speed recordings of vocal fold movement. Basic research focuses on fundamental physical interactions during vocalization based on fluid-structure-acoustic interaction (FSAI). Using numerical (spring-mass and also 3D finite volume models) and experimental (synthetic silicone vocal folds and ex-vivo cadaver animal larynxes) methods, we investigate the relationship between excitatory airflow, vocal fold movement and resulting acoustics for physiological and pathological processes in the larynx. Since 2016, we have been working on the molecular biological analysis of vocal fold tissue. All of this should lead to improved diagnosis and treatment of our patients in the future. Current methods of machine learning (artificial intelligence) are used to develop future quantitative diagnostic procedures. Current methods of machine learning (artificial intelligence) are used to develop future quantitative diagnostic procedures.