Muscle Control Mechanism of Voice Production in Vocal Fold Paralysis

项目摘要 经过近50年的人声研究，关于肌肉的研究仍有许多未知之处 发声的控制机制。研究证实，声带发声前的姿势 (几何、位置、张力和硬度)是控制声带的主要因素之一 振动动力学和声音类型。然而，有关肌肉控制的数据非常有限。 这些特性，主要是由于实验上的困难。声门几何学的肌肉控制 已经在活体人类和动物模型中进行了动力学研究，但这些研究是 仅限于内窥镜俯视，因此不能提供3D变形/移动 声带。此外，声带组织的张力和僵硬很难在 VIVO由于缺乏可靠的技术。关于如何做到这一点，仍然存在显著的知识差距 喉内肌(ILM)也通过声带姿势控制发声。 由于ILM功能障碍，如声带麻痹/轻瘫(VFP)，如何通过 改变声带姿势。在这个项目中，我们建议使用一种创新的方法， 将实验数据和最先进的计算机建模技术集成在一起，生成了一个 3D声带姿势(几何形状、位置、张力、硬度)、3D声带的完整数据集 在整个肌肉控制空间中的振动动力学和声音结果，包括对称， 不对称和补偿性肌肉激活。PI的小组最近开发了一种状态- 这种基于物理的3D计算机模型集成了逼真的喉部解剖结构， 生理上可量化的输入、逆材料参数化和机器学习 模拟发声时的声带姿势和流动-结构-声学相互作用(FSAI) 制作。对于这个项目，我们建议将该具体化模型与实验数据相结合 生成声带姿势和FSAI的整体视图，具有很好的时间和空间 详细信息在完整的肌肉控制空间。特别是，该模型将揭示出 声带姿势和振动，并提供肌肉张力和僵硬的测量 激活，但尚未提供。我们建议使用数据集来阐明因果关系 肌肉活动、声带姿势、声带振动和声音结果之间的联系。肌肉 将识别具有不同姿势、振动和声学模式的组合。新的 知识有望通过以下途径阐明发声的肌肉控制机制 声带姿势。拟议的工作有可能提高对该功能的洞察力 和ILM功能障碍，并作为新的靶向治疗的基础 接近了。我们希望开发可能的生物力学测量方法来诊断和优化 VFP的治疗方法学。

Project Summary After nearly five decades of human voice research, much remains unknown regarding muscle control mechanism of voice production. Studies confirmed that vocal fold pre-phonatory posture (geometry, position, tension and stiffness) is among the primary factors controlling vocal fold vibratory dynamics and voice type. However, very limited data is available on muscle control of these properties, primarily due to experimental difficulties. Muscle control of glottic geometry and dynamics has been studied in in vivo human and animal models, but these studies were limited to an endoscopic superior view, thus cannot to provide 3D deformation/movement of the vocal folds. Moreover, tension and stiffness of the vocal fold tissues are very difficult to obtain in vivo due to a lack of reliable techniques. A significant knowledge gap remains regarding how intrinsic laryngeal muscles (ILMs) control voice production through vocal fold posturing as well as how ILM dysfunctions, such as vocal fold paralysis/paresis (VFP), affect voice production by altering vocal fold posturing. In this project, we propose to use an innovative approach that integrates experimental data and state-of-the-art computer modeling techniques to produce a complete dataset of 3D vocal fold postures (geometry, position, tension, stiffness), 3D vocal fold vibratory dynamics, and voice outcomes in the full muscle control space including symmetric, asymmetric and compensative muscle activations. The PI’s group recently developed a state-of- the-art, physics based, 3D computer model that integrates realistic laryngeal anatomy, physiologically quantifiable inputs, inverse material parameterization and machine learning for simulating vocal fold posturing and flow-structure-acoustics interaction (FSAI) during voice production. For this project, we propose to combine this embodied model with experimental data to generate a holistic view of vocal fold posturing and FSAI with great temporal and spatial details in the full muscle control space. In particular, the model will reveal the 3D complexity of vocal fold postures and vibrations and provide measures of tension and stiffness with muscle activations, which have not been available. We propose to use the dataset to elucidate causal links among muscle activity, vocal fold posturing, vocal fold vibration and voice outcome. Muscle combinations with distinct posturing, vibration and acoustic patterns will be identified. The new knowledge is expected to elucidate the muscle control mechanism of voice production through vocal fold posturing. The proposed work has the potential to improve insight into the function and dysfunction of the ILMs and to serve as a foundation for novel, targeted therapeutic approaches. We hope to develop possible biomechanical metrics for the diagnosis and optimal methodology for treatment of VFP.