Classification of Unilateral Vocal Fold Paralysis by Endoscopic Digital High-Speed Recordings and Inversion of a Biomechanical Model

2006 ◽  
Vol 53 (6) ◽  
pp. 1099-1108 ◽  
Author(s):  
R. Schwarz ◽  
U. Hoppe ◽  
M. Schuster ◽  
T. Wurzbacher ◽  
U. Eysholdt ◽  
...  
Keyword(s):  
Vocal Fold ◽  
High Speed ◽  
Biomechanical Model ◽  
Vocal Fold Paralysis ◽  
Unilateral Vocal Fold Paralysis ◽  
And Inversion

Normal Voice Production: Computation of Driving Parameters from Endoscopic Digital High Speed Images

2003 ◽  
Vol 42 (03) ◽  
pp. 271-276 ◽  
Author(s):  
T. Braunschweig ◽  
J. Lohscheller ◽  
U. Eysholdt ◽  
U. Hoppe ◽  
M. Döllinger
Keyword(s):  
Vocal Fold ◽  
High Speed ◽  
Biomechanical Model ◽  
Vocal Folds ◽  
Inversion Algorithm ◽  
Knowledge Based ◽  
Normal Voice ◽  
Inversion Procedure ◽  
High Speed Glottography

Summary Objectives: A central point for quantitative evaluation of pathological and healthy voices is the analysis of vocal fold oscillations. By means of digital High Speed Glottography (HGG), vocal fold oscillations can be recorded in real time. Recently, a numerical inversion procedure was developed that allows the extraction of physiological parameters from digital high speed videos and a classification of voice disorders. The aim of this work was to validate the inversion procedure and to investigate the applicability to normal voices. Methods: High speed recordings were performed during phonation within a group of five female and five male persons with normal voices. By using knowledge based image processing algorithms, motion curves of the vocal folds were extracted at three different positions (dorsal, medial, ventral). These curves were used to obtain physiological voice parameters, and in particular the degree of symmetry of the vocal folds based upon a biomechanical model of the vocal folds. Results: The highest degree of symmetry was observed for the medial motion curves. While the dor-sally and ventrally extracted motion curves exhibited similar results concerning the degree of symmetry the performance of the algorithm was less stable. Conclusions: The inversion algorithm provides reasonable results for all subjects when applied to the medial motion curves. However, for dorsal and ventral motion curves, correct performance is reduced to 85 %.

scholarly journals Preliminary study of Data Mining analysis of high speed Kymography and voice data

Areté ◽  
2018 ◽  
Vol 18 (2) ◽  
pp. 11-20
Author(s):  
Monike Tsutsumi ◽  
Regina Aparecida Pimienta ◽  
Victor Hugo Cândido de Olivera ◽  
Seiji Isotani ◽  
Alexandre Cláudio Botazzo Delbem ◽  
...  
Keyword(s):  
Data Mining ◽  
Vocal Fold ◽  
High Speed ◽  
External Noise ◽  
Vocal Fold Paralysis ◽  
Future Research ◽  
Unilateral Vocal Fold Paralysis ◽  
Laryngeal Diseases ◽  
Voice Data ◽  
Data Mining Analysis

The use of high-speed laryngeal images technology contributes increasingly to promote greater objectivity in the characterization of laryngeal physiology, as well as, in the diagnosis and monitoring of laryngeal diseases. Vocal fold paralysis is still an unknown incidence, both in Brazil and in the rest of the World, its occurrence has become more frequent in medical and speech-pathologist clinics. Data mining is the process of analyzing hidden patterns of data according to different perspectives for categorization into useful information. In other words, Data Mining is able to identify patterns between information and grouping them according to some given criteria. Objective: To analyze high-speed kymographic images and voice signals with and without unilateral vocal fold paralysis using the data mining computerized system DAMICORE. Methodology: High-speed kymography and acoustic voice signals of subjects with and without unilateral vocal fold paralysis were analyzed by a computerized data mining tool, the DAMICORE system. Results: Data mining analysis for High-speed kymography of healthy individuals gather the groups by sex, while images from subjects with unilateral vocal fold paralysis were gathered by contrast of colors and by light incidence in the images. For voice signals, the technique considered the presence of external noise as a criterion for gathering groups. Conclusion: We concluded that DAMICORE it is a promising tool for kymographic images and voice signal data mining analysis. This tool shown high sensibility to noise in acoustical signals. Consequently, future research should consider this characteristic.

Evaluation of 18F-fluorodeoxyglucose Accumulation in the Larynx of Unilateral Vocal Fold Paralysis Cases

2011 ◽  
Vol 62 (1) ◽  
pp. 11-16
Author(s):  
Yoshitsugu Nimura ◽  
Masahiko Higashikawa ◽  
Terue Okamura ◽  
Ken Nakai ◽  
Kengo Ichihara ◽  
...  
Keyword(s):  
Vocal Fold ◽  
Vocal Fold Paralysis ◽  
Unilateral Vocal Fold Paralysis ◽  
18F Fluorodeoxyglucose

scholarly journals Numerical and Experimental Investigations on Vocal Fold Approximation in Healthy and Simulated Unilateral Vocal Fold Paralysis

2021 ◽  
Vol 11 (4) ◽  
pp. 1817
Author(s):  
Zheng Li ◽  
Azure Wilson ◽  
Lea Sayce ◽  
Amit Avhad ◽  
Bernard Rousseau ◽  
...  
Keyword(s):  
Computational Model ◽  
Vocal Fold ◽  
High Speed ◽  
Computational Models ◽  
Ex Vivo ◽  
Vocal Fold Paralysis ◽  
Future Application ◽  
Experimental Investigations ◽  
Type I ◽  
Mri Scans

We have developed a novel surgical/computational model for the investigation of unilat-eral vocal fold paralysis (UVFP) which will be used to inform future in silico approaches to improve surgical outcomes in type I thyroplasty. Healthy phonation (HP) was achieved using cricothyroid suture approximation on both sides of the larynx to generate symmetrical vocal fold closure. Following high-speed videoendoscopy (HSV) capture, sutures on the right side of the larynx were removed, partially releasing tension unilaterally and generating asymmetric vocal fold closure characteristic of UVFP (sUVFP condition). HSV revealed symmetric vibration in HP, while in sUVFP the sutured side demonstrated a higher frequency (10–11%). For the computational model, ex vivo magnetic resonance imaging (MRI) scans were captured at three configurations: non-approximated (NA), HP, and sUVFP. A finite-element method (FEM) model was built, in which cartilage displacements from the MRI images were used to prescribe the adduction, and the vocal fold deformation was simulated before the eigenmode calculation. The results showed that the frequency comparison between the two sides was consistent with observations from HSV. This alignment between the surgical and computational models supports the future application of these methods for the investigation of treatment for UVFP.

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