Department of Phoniatrics and Pediatric Audiology, University Hospital Erlangen, Bohlenplatz, Erlangen, Germany.
J Voice. 2011 Sep;25(5):576-90. doi: 10.1016/j.jvoice.2010.04.004. Epub 2010 Aug 21.
The aim of this study was to look for visual subjective and objective parameters of vocal fold dynamics being capable of differentiating healthy from pathologic voices in daily clinical practice applying endoscopic high-speed digital imaging (HSI).
Four hundred ninety-six datasets containing 80 healthy and 416 pathologic subjects (232 functional dysphonia (FD), 13 bilateral, and 171 unilateral vocal fold nerve paralysis) were analyzed retrospectively. Videos at 4000Hz (256×256 pixel) were recorded during sustained phonation. Subjective parameters were visually evaluated and complemented by an analysis of objective parameters. Visual subjective parameters were mucosal wave, glottal closure type, glottal closure insufficiency (GI), asymmetries of the vocal folds, and phonovibrogram (PVG) symmetry. After image segmentation, objective parameters were computed: closed quotient, perturbation measures (PMs) of glottal area, and left-right asymmetry values.
HSI evaluation enabled to distinguish healthy from pathologic voices. For visual subjective parameters, GI, symmetrical behavior, and PVG symmetry exhibited statistical significant differences. For 95% of the data, objective parameters could be computed. Among objective parameters, closed quotient, jitter, shimmer, harmonic-to-noise ratio, and signal-to-noise ratio for the glottal area function differentiated statistically significant normal from pathologic voices. Applying linear discriminant analysis by combining visual subjective and objective parameters, accurate classifications were made for 63.2% of the female and 87.5% of the male group for the three-class problem (healthy, FD, and unilateral vocal fold nerve paralysis).
Actual acoustically applied PMs can be transferred to clinical beneficial HSI analysis. Combining visual subjective and objective basic parameters succeeds in differentiating pathologic from healthy voices. The presented evaluation can easily be included into everyday clinical practice. However, further research is needed to broaden our understanding of the variability within and across healthy and pathologic vocal fold vibrations for diagnosing voice disorders and therapy control.
本研究旨在通过应用内镜高速数字成像(HSI)寻找能够在日常临床实践中区分健康与病理嗓音的声带动力学的视觉主观和客观参数。
回顾性分析了包含 80 名健康和 416 名病理受试者(232 名功能性发音障碍(FD)、13 名双侧和 171 名单侧声带神经麻痹)的 496 组数据集。在持续发声期间以 4000Hz(256×256 像素)记录视频。通过视觉评估主观参数,并辅以客观参数分析。主观参数包括黏膜波、声门闭合类型、声门闭合不全(GI)、声带不对称和嗓音声谱图(PVG)对称性。在图像分割后,计算出客观参数:闭合商、声门面积的扰动测量(PMs)和左右不对称值。
HSI 评估能够区分健康与病理嗓音。对于视觉主观参数,GI、对称行为和 PVG 对称性存在统计学显著差异。对于 95%的数据,可以计算出客观参数。在客观参数中,声门面积功能的闭合商、抖动、颤抖、谐噪比和信噪比对正常与病理嗓音的区分具有统计学意义。通过结合视觉主观和客观参数进行线性判别分析,可以对女性的 63.2%和男性的 87.5%组的三分类问题(健康、FD 和单侧声带神经麻痹)进行准确分类。
实际应用于声学的 PMs 可以转化为临床有益的 HSI 分析。结合视觉主观和客观基本参数可以成功区分病理与健康嗓音。所提出的评估可以很容易地纳入日常临床实践。然而,需要进一步研究来拓宽我们对健康和病理声带振动的变异性的理解,以诊断嗓音障碍和治疗控制。