ArticleThe Journal of the Acoustical Society of America2021
A one-dimensional flow model enhanced by machine learning for simulation of vocal fold vibration.
Article in The Journal of the Acoustical Society of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Multi-timescale finite element modeling of vocal fold edema progression due to phonotrauma.The Journal of the Acoustical Society of America · 2026Article
- Standardisation of an AI-based vocal fold assessment tool on a recurrent respiratory papillomatosis model.Acta otorhinolaryngologica Italica : organo ufficiale della Societa italiana di otorinolaringologia e chirurgia cervico-facciale · 2025Article
- Subject-Specific Modeling of Implant Placement for Type I Thyroplasty Surgery.Annals of biomedical engineering · 2023Article
- Subject-Specific Computational Fluid-Structure Interaction Modeling of Rabbit Vocal Fold Vibration.Fluids (Basel, Switzerland) · 2022Article
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Authors and funding
5 authors.
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Abstract
A one-dimensional (1D) unsteady and viscous flow model that is derived from the momentum and mass conservation equations is described, and to enhance this physics-based model, a machine learning approach is used to determine the unknown modeling parameters. Specifically, an idealized larynx model is constructed and ten cases of three-dimensional (3D) fluid-structure interaction (FSI) simulations are performed. The flow data are then extracted to train the 1D flow model using a sparse identification approach for nonlinear dynamical systems. As a result of training, we obtain the analytical expressions for the entrance effect and pressure loss in the glottis, which are then incorporated in the flow model to conveniently handle different glottal shapes due to vocal fold vibration. We apply the enhanced 1D flow model in the FSI simulation of both idealized vocal fold geometries and subject-specific anatomical geometries reconstructed from the magnetic resonance imaging images of rabbits' larynges. The 1D flow model is evaluated in both of these setups and shown to have robust performance. Therefore, it provides a fast simulation tool that is superior to the previous 1D models.
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Registered trials
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