Tobias Wurzbacher

Classification of unilateral vocal fold paralysis by endoscopic digital high-speed recordings and inversion of a biomechanical model

Hoarseness in unilateral vocal fold paralysis is mainly due to irregular vocal fold vibrations caused by asymmetries within the larynx physiology. By means of a digital high-speed camera vocal fold oscillations can be observed in real-time. It is possible to extract the irregular vocal fold oscillations from the high-speed recordings using appropriate image processing techniques. An inversion procedure is developed which adjusts the parameters of a biomechanical model of the vocal folds to reproduce the irregular vocal fold oscillations. Within the inversion procedure a first parameter approximation is achieved through a knowledge-based algorithm. The final parameter optimization is performed using a genetic algorithm. The performance of the inversion procedure is evaluated using 430 synthetically generated data sets. The evaluation results comprise an error estimation of the inversion procedure and show the reliability of the algorithm. The inversion procedure is applied to 15 healthy voice subjects and 15 subjects suffering from unilateral vocal fold paralysis. The optimized parameter sets allow a classification of pathologic and healthy vocal fold oscillations. The classification may serve as a basis for therapy selection and quantification of therapy outcome in case of unilateral vocal fold paralysis.

Spatio-temporal quantification of vocal fold vibrations using high-speed videoendoscopy and a biomechanical model

Pathologic changes within the organic constitution of vocal folds or a functional impairment of the larynx may result in disturbed or even irregular vocal fold vibrations. The consequences are perturbations of the acoustic speech signal which are perceived as a hoarse voice. By means of appropriate image processing techniques, the vocal fold dynamics are extracted from digital high-speed videos. This study addresses the approach to obtain a parametric description of the spatio-temporal characteristics of the vocal fold oscillations for the aim of classification. For this purpose a biomechanical vocal fold model is introduced. An automatic optimization procedure is developed for fitting the model dynamics to the observed vocal fold oscillations. Thus, the resulting parameter values represent a specific vibration pattern and serve as an objective quantification measure. Performance and reliability of the optimization procedure are validated with synthetically generated data sets. The high-speed videos of two normal voice subjects and six patients suffering from different voice disorders are processed. The resulting model parameters represent a rough approximation of physiological parameters along the entire vocal folds.

Spatiotemporal classification of vocal fold dynamics by a multimass model comprising time-dependent parameters

A model-based approach is proposed to objectively measure and classify vocal fold vibrations by left-right asymmetries along the anterior-posterior direction, especially in the case of nonstationary phonation. For this purpose, vocal fold dynamics are recorded in real time with a digital high-speed camera during phonation of sustained vowels as well as pitch raises. The dynamics of a multimass model with time-dependent parameters are matched to vocal fold vibrations extracted at dorsal, medial, and ventral positions by an automatic optimization procedure. The block-based optimization accounts for nonstationary vibrations and compares the vocal fold and model dynamics by wavelet coefficients. The optimization is verified with synthetically generated data sets and is applied to 40 clinical high-speed recordings comprising normal and pathological voice subjects. The resulting model parameters allow an intuitive visual assessment of vocal fold instabilities within an asymmetry diagram and are applicable to an objective quantification of asymmetries.

Calibration of laryngeal endoscopic high-speed image sequences by an automated detection of parallel laser line projections.

High-speed laryngeal endoscopic systems record vocal fold vibrations during phonation in real-time. For a quantitative analysis of vocal fold dynamics a metrical scale is required to get absolute laryngeal dimensions of the recorded image sequence. For the clinical use there is no automated and stable calibration procedure up to now. A calibration method is presented that consists of a laser projection device and the corresponding image processing for the automated detection of the laser calibration marks. The laser projection device is clipped to the endoscope and projects two parallel laser lines with a known distance to each other as calibration information onto the vocal folds. Image processing methods automatically identify the pixels belonging to the projected laser lines in the image data. The line detection bases on a Radon transform approach and is a two-stage process, which successively uses temporal and spatial characteristics of the projected laser lines in the high-speed image sequence. The robustness and the applicability are demonstrated with clinical endoscopic image sequences. The combination of the laser projection device and the image processing enables the calibration of laryngeal endoscopic images within the vocal fold plane and thus provides quantitative metrical data of vocal fold dynamics.