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Extracting vocal fold kinematic parameters from videokymograms via simulation of clinically observed data.

Autoři: Bulusu S., Kumar S.P., Švec J.G., Aichinger P.Publikováno : In: Manfredi C. (ed.), Proceedings MAVEBA 2019: Models and analysis of vocal emissions for biomedical applications. 11th international workshop, 141-144. Firenze University Press, FirenzeRok: 2019

This paper proposes the extraction of vocal fold parameters from videokymographic images. A previously developed model of vocal fold vibrations is generalized to include left-right phase differences and paramedian collisions of the vocal folds. A model fitting error minimization procedure is implemented in order to extract kinematic parameters. 55 clinical and 50 synthetic kymograms are used to evaluate the procedure using the “Structural Dissimilarity Index Measure” (DSSIM) and the “Cross Uncorrelation” (CUC) as error measures. After fitting the clinical kymograms, probability density functions (PDFs) of the model parameters are obtained. The PDFs are used to generate synthetic kymograms with random parameters. The synthetic kymograms are used to evaluate the performance of the fitting procedure by measuring the errors between the randomly generated parameter values and those obtained through the fitting procedure. The relative error ranged between 0.052% and 44.95%.


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