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Optimization and automation of relative fundamental frequency for objective assessment of vocal hyperfunction.

机译:相对基频的优化和自动化,用于客观评估声带功能。

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摘要

The project objective is to improve clinical assessment and diagnosis of the voice disorder, vocal hyperfunction (VH). VH is a condition characterized by excessive laryngeal and paralaryngeal tension, and is assumed to be the underlying cause of the majority of voice disorders. Current clinical assessment of VH is subjective and demonstrates poor inter-rater reliability. Recent work indicates that a new acoustic measure, relative fundamental frequency (RFF) is sensitive to the maladaptive functional behaviors associated with VH and can potentially be used to objectively characterize VH.;Here, we explored and enhanced the potential for RFF as a measure of VH in three ways. First, the current protocol for RFF estimation was optimized to simplify the recording procedure and reduce estimation time. Second, RFF was compared with the current state-of-the-art measures of VH -- listener perception of vocal effort and the aerodynamic ratio of sound pressure level to subglottal pressure level. Third, an automated algorithm that utilized the optimized recording protocol was developed and validated against manual estimation methods and listener perception. This work enables large-scale studies on RFF to determine the specific physiological elements that contribute to the measure's ability to capture VH and may potentially provide a non-invasive and readily implemented solution for this long-standing clinical issue.
机译:该项目的目标是改善对声音障碍,声带功能亢进(VH)的临床评估和诊断。 VH是一种以喉咙和旁咽过度紧张为特征的疾病,被认为是大多数声音障碍的根本原因。当前对VH的临床评估是主观的,并表明评分者之间的可靠性差。最近的工作表明,一种新的声学测量方法,相对基频(RFF)对与VH相关的适应不良的功能行为敏感,可以潜在地用于客观地表征VH。在此,我们探索并增强了RFF作为测量VH的潜力。 VH有三种方式。首先,对当前的RFF估计协议进行了优化,以简化记录过程并减少估计时间。其次,将RFF与VH的最新技术进行了比较-听众对声音的感知以及声压级与声门下压力级的空气动力学比。第三,开发了一种利用优化记录协议的自动算法,并针对手动估算方法和听众感知进行了验证。这项工作使得能够对RFF进行大规模研究,以确定有助于该方法捕获VH的特定生理因素,并可能为这一长期存在的临床问题提供非侵入性且易于实施的解决方案。

著录项

  • 作者

    Lien, Yu-An Stephanie.;

  • 作者单位

    Boston University.;

  • 授予单位 Boston University.;
  • 学科 Biomedical engineering.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 187 p.
  • 总页数 187
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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