TY - EJOU
AU - Faizal, W. M.
AU - Ghazali, N. N. N.
AU - Khor, C. Y.
AU - Zainon, M. Z.
AU - Badruddin, Irfan Anjum
AU - Kamangar, Sarfaraz
AU - Ibrahim, Norliza Binti
AU - Razi, Roziana Mohd
TI - Computational Analysis of Airflow in Upper Airway under Light and Heavy Breathing Conditions for a Realistic Patient Having Obstructive Sleep Apnea
T2 - Computer Modeling in Engineering \& Sciences
PY - 2021
VL - 128
IS - 2
SN - 1526-1506
AB - Background: Obstructive sleep apnea is a sleeping disorder that has troubled a sizeable population. There is an
active area of research on obstructive sleep apnea that intends to better understand airflow behaviors and therefore
treat patients more effectively. This paper aims to investigate the airflow characteristics of the upper airway in
an obstructive sleep apnea (OSA) patient under light and heavy breathing conditions by using Turbulent Kinetic
Energy (TKE), an accurate method in expressing the flow concentration mechanisms of sleeping disorders. It is
important to visualize the concentration of flow in the upper airway in order to identify the severity level of the
obstruction during sleep. Methods: Computational fluid dynamic (CFD) analysis was used as a solution tool to
evaluate the airflow during light and heavy breathing conditions. A medical imaging technique was used to extract
the 3D model from the CT scan images. Additionally, mesh generation and simulation were carried out via CFD
software to evaluate the light and heavy breathing characteristics related to obstructive sleep apnea. Steady state
Reynold’s averaged Navier-Stoke (RANS) with the k-ω shear stress transport (SST) turbulence model was utilized.
The airflow characteristics were quantified using parameters such as pressure distribution, skin friction coefficient,
velocity profile, Reynolds number, turbulent Reynolds number and turbulence kinetic energy. Results: Contour
plots at different planes were used to visualize the airflow distribution as it passed through different cross-sectional
areas of the airway. The results revealed that the presence of a smaller cross-sectional area of the airway caused an
increase in airflow parameters, especially during heavy breathing. Furthermore, turbulent airflow conditions along
the airway were noticed during heavy breathing. The severity of OSA could be measured by the turbulent kinetic
energy which is able to show the behavior and concentration of mean flow. This study is expected to provide crucial
and important results by visualizing the concentration of airflow mechanisms and characteristics of a patient’s airway during light and heavy breathing. These findings enable TKE to be used as a new tool for characterizing the
severity of obstructive sleep apnea in the upper airways of patients.
KW - Human upper airway; computational fluid dynamics; obstructive sleep apnea; turbulent kinetic energy
DO - 10.32604/cmes.2021.015549