OBJECTIVES/HYPOTHESIS: Quantitative analysis of endoscopic high-speed video recordings of vocal fold vibrations has been growing in importance in recent years. The videos have mainly been analyzed using subjective evaluation, but this is examiner dependent, and the results show inadequate interobserver agreement. The aims of this study were therefore to identify appropriate objective parameters for analyzing high-speed recordings to differentiate healthy voice production from organic disorders. METHODS: A total of 152 females were examined, divided into 77 healthy and 75 with four different pathological conditions: laryngeal epithelial thickening, Reinke edema, vocal fold polyps, and vocal fold cysts. Vocal fold vibrations were recorded with a high-speed camera (4,000 Hz, 256 × 256 pixels) during sustained phonation. Parameters computed from the glottal area waveform (GAW) and from phonovibrogram (PVG) were analyzed. Multiparametric linear discriminant analysis was performed to classify pathological conditions versus the healthy group. RESULTS: Twenty of 44 parameters were identified that are capable of distinguishing between the individual types of pathology. PVG parameters showed better performance than GAW parameters. Parameters representing vibrational periodicity via standard deviation showed better performance than absolute parameters. In addition, linear discriminant analysis achieved reliable differentiation between healthy and pathological vocal fold vibrations: 72% for the five-class problem (all groups separately) and 88% for the two-class problem (healthy vs. all pathologies taken as one class). CONCLUSIONS: The study succeeded in defining objective parameters for analyzing endoscopic high-speed videos and suggesting first parameters for differentiation between healthy dynamics and dynamics of organic pathologies.
OBJECTIVES/HYPOTHESIS: Quantitative analysis of endoscopic high-speed video recordings of vocal fold vibrations has been growing in importance in recent years. The videos have mainly been analyzed using subjective evaluation, but this is examiner dependent, and the results show inadequate interobserver agreement. The aims of this study were therefore to identify appropriate objective parameters for analyzing high-speed recordings to differentiate healthy voice production from organic disorders. METHODS: A total of 152 females were examined, divided into 77 healthy and 75 with four different pathological conditions: laryngeal epithelial thickening, Reinke edema, vocal fold polyps, and vocal fold cysts. Vocal fold vibrations were recorded with a high-speed camera (4,000 Hz, 256 × 256 pixels) during sustained phonation. Parameters computed from the glottal area waveform (GAW) and from phonovibrogram (PVG) were analyzed. Multiparametric linear discriminant analysis was performed to classify pathological conditions versus the healthy group. RESULTS: Twenty of 44 parameters were identified that are capable of distinguishing between the individual types of pathology. PVG parameters showed better performance than GAW parameters. Parameters representing vibrational periodicity via standard deviation showed better performance than absolute parameters. In addition, linear discriminant analysis achieved reliable differentiation between healthy and pathological vocal fold vibrations: 72% for the five-class problem (all groups separately) and 88% for the two-class problem (healthy vs. all pathologies taken as one class). CONCLUSIONS: The study succeeded in defining objective parameters for analyzing endoscopic high-speed videos and suggesting first parameters for differentiation between healthy dynamics and dynamics of organic pathologies.
Authors: Anne Schützenberger; Melda Kunduk; Michael Döllinger; Christoph Alexiou; Denis Dubrovskiy; Marion Semmler; Anja Seger; Christopher Bohr Journal: Biomed Res Int Date: 2016-11-21 Impact factor: 3.411
Authors: Patrick Schlegel; Andreas M Kist; Melda Kunduk; Stephan Dürr; Michael Döllinger; Anne Schützenberger Journal: PLoS One Date: 2021-02-02 Impact factor: 3.240