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.

发音障碍在与构音障碍的谈话者中很常见，并且已被证明对 语音清晰度损失。但是，关节损伤的治疗仍然具有挑战性。主要是 因为有关发音障碍模式及其在谈话者之间的不同知识是有限的。这 Mayo诊所构音障碍分类系统将神经系统条件与特定的听觉联系起来 定义的构音障碍类型可能具有不同的运动障碍模式。基于此框架， 突出的教科书建议专门针对大概是基础的运动障碍 每种构音症类型。但是，这种干预方法仍然缺乏经验支持，很难 适用于混合构造障碍类型。基于这样的理由，即几乎所有患有构想障碍的谈话者都表现出不精确的 发音，障碍非特异性行为治疗（例如，响亮，清晰，言语缓慢）已获得 受欢迎程度，通常用作轻度至中度构音障碍的说话者的治疗干预措施 不管它们的潜在疾病。然而，这种理由忽略了这样一个事实，即各种发音 行为可以产生相同的听觉感知后果。确实，高度异质的关节 据报道，疾病类型的绩效模式已有报道，并激发了我们测试 基于语音运动学的新型分类学（数据驱动）方法的可行性 措施。我们在28个与帕金森氏病（PD）的谈话者组成的同类中，肌萎缩性侧索硬化症 （ALS）和多发性硬化症（MS）揭示了六个具有独特关节损伤的构音症亚组 解决声带调整的时间和空间特征以及唇轴耦合的轮廓。 确定了三个疾病主导的亚组和三个混合疾病亚组。这提出了 项目旨在扩大这些初步发现。在特定的目标1中，我们将对关节进行分类 有不同潜在疾病类型的160位谈话者的性能概况[PD，ALS，MS，亨廷顿氏病 （高清）]。为了允许对运动学发现的临床解释，说话者的表达性能 构造障碍将参考年龄和性别特异性对照组。我们还将确定哪种运动学 衡量说话者与构音障碍和疾病类型在整个关节中有系统不同的说话者 - 基于构音障碍亚组。确保将基于运动学的分类方法快速翻译成 临床实践我们将确定如何基于感知的临床临床评级到 运动学措施的结果（特定目标2）。评估者将判断相同160的旋转性能 使用听觉和视觉感知评级尺度的构造障碍的说话者。研究成果将进步 田野对发音损伤模式的理解以及它们在构音障碍中的变化。发现对 阐明了可理解性丧失和恢复的亚组特异性关节机制。最终，这项工作将 促进个性化构音障碍管理和新的，特定于减值的干预措施的发展。