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通过内镜数字高速记录和生物力学模型反演对单侧声带麻痹进行分类

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

作者信息

Schwarz Raphael, Hoppe Ulrich, Schuster Maria, Wurzbacher Tobias, Eysholdt Ulrich, Lohscheller Jörg

机构信息

Department of Phoniatrics and Pediatric Audiology, University of Erlangen-Nürnberg, Germany.

出版信息

IEEE Trans Biomed Eng. 2006 Jun;53(6):1099-108. doi: 10.1109/TBME.2006.873396.

Abstract

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.

摘要

单侧声带麻痹引起的声音嘶哑主要是由于喉生理结构不对称导致声带振动不规则所致。借助数字高速摄像机,可以实时观察声带振荡情况。利用适当的图像处理技术,能够从高速记录中提取不规则的声带振荡。开发了一种反演程序,该程序调整声带生物力学模型的参数,以再现不规则的声带振荡。在反演程序中,通过基于知识的算法实现初始参数近似。最终的参数优化使用遗传算法进行。使用430个合成生成的数据集评估反演程序的性能。评估结果包括反演程序的误差估计,并显示了该算法的可靠性。将反演程序应用于15名健康嗓音受试者和15名单侧声带麻痹患者。优化后的参数集可用于对病理性和健康的声带振荡进行分类。这种分类可为单侧声带麻痹的治疗选择和治疗效果量化提供依据。

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