Muscle Control Mechanism of Voice Production in Vocal Fold Paralysis

项目摘要 经过近50年的人类发声研究，关于肌肉控制机制仍有许多未知之处 声音制作的关键。研究证实，声带发声前的姿势(几何、位置、张力和 僵硬)是控制声带振动动力学和声音类型的主要因素之一。然而，非常 关于这些特性的肌肉控制的数据有限，主要是由于实验困难。肌肉 声门几何和动力学的控制已经在活体人类和动物模型中进行了研究，但这些研究 仅限于内窥镜俯视，因此不能提供声带的3D变形/运动。 此外，声带组织的张力和僵硬很难在体内获得，因为缺乏可靠的 技巧。关于喉部固有肌肉(ILM)是如何控制声音的，仍然存在着显著的知识空白 通过声带姿势产生以及ILM功能障碍，如声带瘫痪/轻瘫 (VFP)，通过改变声带姿势来影响发声。 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技术相结合 计算机建模技术以产生3D声带姿势(几何形状，位置， 张力、僵硬)、3D声带振动动力学和完全肌肉控制空间中的声音结果 包括对称性、非对称性和补偿性肌肉激活。PI的小组最近开发了一种 最先进的、基于物理的3D计算机模型，从生理上集成了逼真的喉部解剖结构 模拟声带姿势的可量化输入、逆材料参数化和机器学习 以及发声过程中的流-结构-声学相互作用(FSAI)。对于这个项目，我们建议将 这个具体化的模型具有实验数据，以生成声带姿势和FSAI的整体视图 在完整的肌肉控制空间中提供出色的时间和空间细节。特别是，该模型将揭示3D 声带姿势和振动的复杂性，并提供肌肉张力和僵硬的测量 激活，但尚未提供。 我们建议使用该数据集来阐明肌肉活动、声带姿势、声带之间的因果联系 振动和声音结果。具有不同姿势、振动和声音模式的肌肉组合将 已确认身份。这一新知识有望阐明发声的肌肉控制机制 通过声带姿势。拟议的工作有可能提高对功能和 这将有助于改善ILM的功能障碍，并为新的、有针对性的治疗方法奠定基础。我们希望 开发诊断VFP的可能生物力学指标和治疗VFP的最佳方法。

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.