A taxonomic articulation-focused approach to dysarthria classification

以分类学发音为重点的构音障碍分类方法

• 批准号: 10685349
• 负责人: Antje Mefferd
• 金额: $ 54.58万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-17 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10685349
• 关键词: Address; Affect; Age; Amyotrophic Lateral Sclerosis; Articulation; Auditory; Behavior; Behavior Therapy; Characteristics; Classification; Clinic; Clinical; Cluster Analysis; Control Groups; Coupling; Cueing for speech; Data; Development; Disease; Dysarthria; Ensure; Exhibits; Goals; Grain; Huntington Disease; Hypokinesia; Impairment; Infrastructure; Intervention; Jaw; Knowledge; Link; Lip structure; Loudness; Maps; Measures; Mission; Mixed Dysarthrias; Motor; Movement; Multiple Sclerosis; National Institute on Deafness and Other Communication Disorders; Neurodegenerative Disorders; Neurologic; Outcome; Outcome Study; Parkinson Disease; Pattern; Performance; Positioning Attribute; Posture; Public Health; Reading; Recommendation; Recovery; Reporting; Research; Social isolation; Speech; Speech Intelligibility; Subgroup; System; Taxonomy; Textbooks; Therapeutic Intervention; Tongue; Translations; United States National Institutes of Health; Video Recording; Visual; Work; career; clinical practice; cohort; design; disorder subtype; feasibility testing; impression; improved; kinematics; motor impairment; sex; virtual

Articulatory impairments are common in talkers with dysarthria and have been shown to contribute most to speech intelligibility loss. However, the treatment of articulatory impairments remains challenging; primarily, because knowledge about articulatory impairment patterns and how they vary across talkers is limited. The Mayo Clinic dysarthria classification system links neurological conditions to specific, auditory-perceptually defined dysarthria types with presumably distinct motor impairment patterns. Based on this framework, prominent textbooks have recommended to specifically target the motor impairments that presumably underlie each dysarthria type. Such an intervention approach, however, still lacks empirical support and is difficult to apply to mixed dysarthria types. Based on the rationale that virtually all talkers with dysarthria exhibit imprecise articulation, impairment-nonspecific behavioral treatments (e.g., loud, clear, slow speech) have gained popularity and are commonly used as therapeutic interventions for talkers with mild to moderate dysarthria regardless of their underlying disease. This rationale, however, ignores the fact that a variety of articulatory behaviors can yield the same auditory-perceptual consequences. Indeed, highly heterogeneous articulatory performance patterns have been reported across and within disease types and motivated us to test the feasibility of a new, taxonomic (data-driven) approach to dysarthria classification based on speech kinematic measures. Our pilot work on a cohort of 28 talkers with Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS) revealed six dysarthria subgroups with unique articulatory impairment profiles addressing temporal and spatial characteristics of vocal tract adjustments as well as labial coupling. Three disease-dominant subgroups and well as three mixed-disease subgroups were identified. This proposed project seeks to expand upon these preliminary findings. In Specific Aim 1, we will classify the articulatory performance profiles of 160 talkers with varying underlying disease types [PD, ALS, MS, Huntington's disease (HD)]. To allow for a clinical interpretation of the kinematic findings, articulatory performance of talkers with dysarthria will be referenced to age- and sex-specific control groups. We will also determine which kinematic measures differentiate talkers with dysarthria and if disease-type varies systematically across articulation- based dysarthria subgroups. To ensure a rapid translation of our kinematic-based classification approach into clinical practice we will determine how perceptual-based clinical ratings of articulatory performance map onto findings of kinematic measures (Specific Aim 2). Raters will judge the articulatory performance of the same 160 talkers with dysarthria using auditory- and visual-perceptual ratings scales. Study outcomes will advance the field's understanding of articulatory impairment patterns and how they vary in dysarthria. Findings are critical to elucidate subgroup-specific articulatory mechanisms of intelligibility loss and recovery. Ultimately, this work will facilitate personalized dysarthria management and the development of new, impairment-specific interventions.

发音障碍在构音障碍的说话者中很常见， 语音清晰度损失。然而，发音障碍的治疗仍然具有挑战性;主要是， 因为有关发音障碍模式以及它们在说话者之间如何变化的知识有限。的 马约诊所的构音障碍分类系统将神经系统疾病与特定的、可感知的 定义的构音障碍类型，可能具有不同的运动障碍模式。基于这一框架， 著名的教科书建议专门针对运动障碍， 每种构音障碍类型。然而，这种干预方法仍然缺乏经验支持，难以实施。 适用于混合型构音障碍。基于基本原理，几乎所有的说话者与构音障碍表现出不精确的 发音，损伤-非特异性行为治疗（例如，大声，清晰，缓慢的讲话）获得了 受欢迎，通常用作轻度至中度构音障碍患者的治疗干预 不管他们的潜在疾病。然而，这种理论忽视了一个事实，即各种发音 行为可以产生相同的认知后果。事实上，高度异质的发音 在不同疾病类型之间和疾病类型内报告了表现模式，并促使我们测试 基于语音运动学的构音障碍分类的新的分类学（数据驱动）方法的可行性 措施我们对28名帕金森病（PD）、肌萎缩性侧索硬化症（ALS） (ALS)和多发性硬化症（MS）揭示了6个构音障碍亚组， 描述声道调整以及唇耦合的时间和空间特征的曲线。 确定了三个疾病主导亚组和三个混合疾病亚组。这一拟议 该项目旨在扩大这些初步调查结果。在具体目标1中，我们将对发音进行分类 160名具有不同潜在疾病类型[PD、ALS、MS、亨廷顿病]的谈话者的性能概况 （HD）]。为了对运动学结果进行临床解释， 构音障碍将参照年龄和性别特异性对照组。我们还将确定 措施区分说话者与构音障碍，如果疾病类型不同，系统地跨关节- 构音障碍亚组。为了确保将我们基于运动学的分类方法快速转化为 临床实践中，我们将确定如何感知为基础的临床评级的发音性能映射到 运动学测量结果（具体目标2）。评分员将对同一160名学生的发音表现进行评判， 使用听觉和视觉感知等级量表对构音障碍的说话者进行评估。研究结果将推动 field对发音障碍模式的理解以及它们在构音障碍中的变化。这些发现对于 阐明可懂度损失和恢复的亚组特异性发音机制。最终，这项工作将 促进个性化的构音障碍管理和新的，损伤特定的干预措施的发展。