Modeling the pharyngeal anatomical effects on breathing resistance and aerodynamically generated sound

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• 作者：Jinxiang Xi (1)
  Xiuhua Si (2)
  JongWon Kim (1)
  Guoguang Su (3)
  Haibo Dong (4)
  
• 关键词：Pharyngeal anatomy ; Uvula ; Breathing resistance ; Snoring ; Breathing ; related sleep disorders
• 刊名：Medical and Biological Engineering and Computing
• 出版年：2014
• 出版时间：July 2014
• 年：2014
• 卷：52
• 期：7
• 页码：567-577
• 全文大小：
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• 作者单位：Jinxiang Xi (1)
  Xiuhua Si (2)
  JongWon Kim (1)
  Guoguang Su (3)
  Haibo Dong (4)
  
  1. School of Engineering and Technology, Central Michigan University, 1200 South Franklin Street, Mount Pleasant, MI, 48858, USA
  2. Department of Engineering, Calvin College, Grand Rapids, MI, USA
  3. American Bureau of Shipping, Houston, TX, USA
  4. Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA, USA
  
• ISSN：1741-0444

文摘

The objective of this study was to systematically assess the effects of pharyngeal anatomical details on breathing resistance and acoustic characteristics by means of computational modeling. A physiologically realistic nose-throat airway was reconstructed from medical images. Individual airway anatomy such as the uvula, pharynx, and larynx was then isolated for examination by gradually simplifying this image-based model geometry. Large eddy simulations with the FW-H acoustics model were used to simulate airflows and acoustic sound generation with constant flow inhalations in rigid-walled airway geometries. Results showed that pharyngeal anatomical details exerted a significant impact on breathing resistance and energy distribution of acoustic sound. The uvula constriction induced considerably increased levels of pressure drop and acoustic power in the pharynx, which could start and worsen snoring symptoms. Each source anatomy was observed to generate a unique spectrum with signature peak frequencies and energy distribution. Moreover, severe pharyngeal airway narrowing led to an upward shift of sound energy in the high-frequency range. Results indicated that computational aeroacoustic modeling appeared to be a practical tool to study breathing-related disorders. Specifically, high-frequency acoustic signals might disclose additional clues to the mechanism of apneic snoring and should be included in future acoustic studies.