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.

发音障碍在有构音障碍的说话者中很常见，并已被证明是导致发音障碍的主要原因 语音清晰度丧失。然而，关节损伤的治疗仍然具有挑战性；主要是， 因为对发音障碍模式及其在说话者之间的差异的了解是有限的。这个 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 明确构音障碍类型，推测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可能是潜在的运动障碍 每种构音障碍类型。然而，这种干预方法仍然缺乏经验支持，很难 适用于混合型构音障碍。基于几乎所有有构音障碍的说话者表现出的不精确的原理 发音障碍-非特异性行为治疗(例如，大声、清晰、缓慢的讲话)得到了改善 它很受欢迎，通常用于轻度到中度构音障碍的说话者的治疗干预 不管他们的潜在疾病是什么。然而，这一逻辑忽略了这样一个事实，即各种发音 行为可以产生同样的听觉-知觉后果。事实上，高度不同的发音 已经报告了跨疾病类型和疾病类型内的性能模式，并激励我们测试 基于语音运动学的构音障碍分类(数据驱动)新方法的可行性 措施。我们的试点研究对象是28名帕金森氏病(PD)、肌萎缩侧索硬化症患者 (ALS)和多发性硬化症(MS)显示有6个构音障碍亚群具有独特的关节功能障碍 介绍声道调节的时间和空间特征以及唇部耦合。 共鉴定出3个疾病显性亚群和3个混合病亚群。这项建议 该项目寻求在这些初步发现的基础上进行扩展。在具体目标1中，我们将对发音进行分类 160名具有不同基础疾病类型[帕金森氏病、肌萎缩侧索硬化症、多发性硬化症、亨廷顿病]的说话者的表现特征 (HD)]。为了对运动学发现进行临床解释，说话者的发音能力 构音障碍将指年龄和性别特定的对照组。我们还将确定哪种运动学 测量方法区分发音障碍的说话者，如果疾病类型在发音上有系统地变化- 构音障碍亚组。为了确保我们的基于运动学的分类方法快速转换为 临床实践我们将确定基于感知的临床关节功能分级如何映射到 运动学测量结果(具体目标2)。评分者将评判相同160个单词的发音性能 有构音障碍的说话者使用听觉和视觉知觉评分表。研究结果将推动 菲尔德对构音障碍的发音障碍模式及其变化的理解。调查结果对 阐明亚组特有的清晰度丧失和恢复的发音机制。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损伤的干预措施。