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: 10522517
• 负责人: Antje Mefferd
• 金额: $ 59.89万
• 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/10522517
• 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; Lead; 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; 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; base; 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.

发音障碍在患有构音障碍的说话者中很常见，并且已被证明是造成构音障碍的主要原因 言语清晰度损失。然而，关节损伤的治疗仍然具有挑战性。主要是， 因为关于发音障碍模式及其在不同说话者之间的差异的知识是有限的。这 梅奥诊所构音障碍分类系统将神经系统疾病与特定的听觉感知联系起来 定义的构音障碍类型可能具有不同的运动障碍模式。基于这个框架， 著名教科书建议专门针对可能潜在的运动障碍 每种构音障碍类型。但这种干预方式仍缺乏实证支持，难以实施。 适用于混合型构音障碍。基于几乎所有患有构音障碍的说话者都表现出不精确的基本原理 清晰度、障碍-非特异性行为治疗（例如大声、清晰、缓慢的言语）已获得 受欢迎，通常用作患有轻度至中度构音障碍的说话者的治疗干预措施 无论他们的潜在疾病如何。然而，这一基本原理忽略了这样一个事实：各种发音 行为可以产生相同的听觉感知结果。事实上，高度异质的发音 跨疾病类型和疾病类型内的表现模式已被报道，并促使我们测试 基于言语运动学的构音障碍分类的新分类学（数据驱动）方法的可行性 措施。我们对 28 名患有帕金森病 (PD) 和肌萎缩侧索硬化症的谈话者进行了试点工作 (ALS) 和多发性硬化症 (MS) 揭示了六个具有独特发音障碍的构音障碍亚组 配置文件解决声道调整以及唇耦合的时间和空间特征。 确定了三个主要疾病亚组和三个混合疾病亚组。这个提议 项目力求扩展这些初步发现。在具体目标 1 中，我们将对关节进行分类 160 名患有不同潜在疾病类型的演讲者的表现概况 [PD、ALS、MS、亨廷顿病 （高清）]。为了对运动学结果、说话者的发音表现进行临床解释 构音障碍将参考特定年龄和性别的对照组。我们还将确定哪种运动学 测量方法可以区分患有构音障碍的说话者，以及疾病类型是否在发音过程中系统性地变化—— 基于构音障碍的亚组。确保我们基于运动学的分类方法快速转化为 临床实践中，我们将确定基于感知的发音表现临床评级如何映射到 运动学测量结果（具体目标 2）。评分者将评判相同 160 的发音表现 使用听觉和视觉感知评级量表对患有构音障碍的说话者进行评估。研究成果将推动 领域对发音障碍模式及其在构音障碍中的变化的理解。研究结果至关重要 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 促进个性化构音障碍管理和开发新的针对特定障碍的干预措施。