123 research outputs found

    Computational fluid dynamics in the upper airway: comparison between different models and experimental data for a simplified geometry with major obstruction

    No full text
    The present study aims at comparing different computational models used for simulating the fluid-structure interaction within an in-vitro setup resembling simplified major obstruction of pharyngeal airway. Due to the nature of the problem, i.e. air flow passing over a deformable latex surface, a fully coupled fluid-structure interaction algorithm is used. A comparison is made between two finite element models for the solid domain, one using shell and the other using volume elements. The material properties of these models follow a hyperelastic behavior. For the fluid part, laminar and various turbulence models such as standard k-epsilon, Shear Stress Transport, SSG Reynolds Stress and BSL Reynolds Stress are compared. We evaluate the efficiency of the models and how close to the experimental data are their results. The predictions of the structural model containing volume elements showed better consistency with the experimental data. In addition, the results obtained with the standard k-epsilon turbulence model were the least deviated among all turbulence models

    Biomechanical Models of Human Upper and Tracheal Airway Functionality

    Get PDF
    The respiratory tract, in other words, the airway, is the primary airflow path for several physiological activities such as coughing, breathing, and sneezing. Diseases can impact airway functionality through various means including cancer of the head and neck, Neurological disorders such as Parkinson\u27s disease, and sleep disorders and all of which are considered in this study. In this dissertation, numerical modeling techniques were used to simulate three distinct airway diseases: a weak cough leading to aspiration, upper airway patency in obstructive sleep apnea, and tongue cancer in swallow disorders. The work described in this dissertation, therefore, divided into three biomechanical models, of which fluid and particulate dynamics model of cough is the first. Cough is an airway protective mechanism, which results from a coordinated series of respiratory, laryngeal, and pharyngeal muscle activity. Patients with diminished upper airway protection often exhibit cough impairment resulting in aspiration pneumonia. Computational Fluid Dynamics (CFD) technique was used to simulate airflow and penetrant behavior in the airway geometry reconstructed from Computed Tomography (CT) images acquired from participants. The second study describes Obstructive Sleep Apnea (OSA) and the effects of dilator muscular activation on the human retro-lingual airway in OSA. Computations were performed for the inspiration stage of the breathing cycle, utilizing a fluid-structure interaction (FSI) method to couple structural deformation with airflow dynamics. The spatiotemporal deformation of the structures surrounding the airway wall was predicted and found to be in general agreement with observed changes in luminal opening and the distribution of airflow from upright to supine posture. The third study describes the effects of cancer of the tongue base on tongue motion during swallow. A three-dimensional biomechanical model was developed and used to calculate the spatiotemporal deformation of the tongue under a sequence of movements which simulate the oral stage of swallow

    A computational neuromuscular model of the human upper airway with application to the study of obstructive sleep apnoea

    Get PDF
    Includes bibliographical references.Numerous challenges are faced in investigations aimed at developing a better understanding of the pathophysiology of obstructive sleep apnoea. The anatomy of the tongue and other upper airway tissues, and the ability to model their behaviour, is central to such investigations. In this thesis, details of the construction and development of a three-dimensional finite element model of soft tissues of the human upper airway, as well as a simplified fluid model of the airway, are provided. The anatomical data was obtained from the Visible Human Project, and its underlying micro-histological data describing tongue musculature were also extracted from the same source and incorporated into the model. An overview of the mathematical models used to describe tissue behaviour, both at a macro- and microscopic level, is given. Hyperelastic constitutive models were used to describe the material behaviour, and material incompressibility was accounted for. An active Hill three-element muscle model was used to represent the muscular tissue of the tongue. The neural stimulus for each muscle group to a priori unknown external forces was determined through the use of a genetic algorithm-based neural control model. The fundamental behaviour of the tongue under gravitational and breathing-induced loading is investigated. The response of the various muscles of the tongue to the complex loading developed during breathing is determined, with a particular focus being placed to that of the genioglossus. It is demonstrated that, when a time-dependent loading is applied to the tongue, the neural model is able to control the position of the tongue and produce a physiologically realistic response for the genioglossus. A comparison is then made to the response determined under quasi-static conditions using the pressure distribution extracted from computational fluid-dynamics results. An analytical model describing the time-dependent response of the components of the tongue musculature most active during oral breathing is developed and validated. It is then modified to simulate the activity of the tongue during sleep and under conditions relating to various possible neural and physiological pathologies. The retroglossal movement of the tongue resulting from the pathologies is quantified and their role in the potential to induce airway collapse is discussed

    Effect of Orthognathic Surgery on the Upper Airway System

    Get PDF
    Sleep apnea is a disease which has not been getting an adequate amount of attention in the research community for a long time. However, the strain on the cardiovascular system and other serious problems, such as daytime sleepiness and even neurocognitive dysfunction, that it causes may be severe in advanced cases of the illness, as such it can significantly affect the heart especially and lead to cardiac arrest. Thus, it has been receiving a lot of attention recently. Tampere University Hospital has a goal of creating a comprehensive upper airway airflow model for surgery outcome prediction. That requires knowledge of available models and analysis of static magnetic resonance images, among other things. This document deals with these two main issues. This thesis has two major parts, one of them being a literature review of sleep apnea and models used in airflow modelling in the upper airways. Modelling of airflow generally includes acquisition of a static upper airway system model (in the case of upper airway modelling) and then adding a dynamic component to it. The second part of this thesis deals with acquisition of the static model, which involves segmentation of MRI image sets from 3 patients (pre- and post-operative sequences). It also answers the question, whether the effect of orhtognathic surgery on the upper airway system can be seen from volumetric analysis of the segmented images and the segmented images themselves. The main methods of adding a dynamic component to the static model turned out to be computational fluid mechanics and finite element modelling, including their sub-methods, such as direct numerical simulation of large eddy simulation. As with the second part of the thesis, the volumetric segmentation data is rather inconclusive and should not be related solely for evaluation of the effect of orthognathic surgery on the upper airway system. It can be said, nonetheless, that the volume of the upper airway itself is rather easily obtainable and reliable. The images themselves, however, provide very visual information about that, and shifting of certain muscles and muscle groups and other structures can be seen

    疾患鼻気道における空気流と粒子堆積の計算流体力学的研究

    Get PDF
    Understanding the properties of airflow in the nasal cavity is very important in determining the nasal physiology and in diagnosis of various anomalies associated with the nose. The complex anatomy of the nasal cavity has proven to be a significant obstacle in the understanding of nasal obstructive disorders. Due to their non-invasiveness, Computational Fluid Dynamics (CFD) has now been utilized to assess the effects of surgical interventions on nasal morphological changes as well as local breathing airflow characteristics through the upper airway of individual patients. Furthermore, nasal inhalation is a major route of entry into body for airborne pollutions. Therefore, the function of the upper airway to filter out the inhaled toxic particles is considered important. The determination of the total particle filtering efficiency and the precise location of the induced lesion in the upper airway is the first step in understanding the critical factors involved in the pathogenesis of the upper airway injury. The present work involved development of three-dimensional diseased upper airway models from Computed Tomographic (CT) scan images derived from a nasal airway without any nasal diseased and an upper airway which was diagnosed with chronic nasal obstruction and obstructive sleep apnea. Numerical simulation of airflow and transport and deposition of inhaled pollutant through chronic diseased nasal airway, constricted pharyngeal representing Obstructive Sleep Apnea (OSA) and diseased upper airway with OSA for pre- and post-operative cases have been studied. Detailed flow pattern and characteristics for inspiratory airflow for various breathing rates (7.5-40 L/min) were evaluated. Simulation of the particle transport and deposition of micro-sized particles with particle diameter ranging from 1-40 ?m were also investigated. In the first part of this study, the surgical treatment performed in the nasal cavity which include septoplasty, inferior turbinate reduction and partial concha bullosa resection substantially increased nasal volume, which influenced flow partitioning and decreases the pressure drop and flow resistance of the nasal passage. The removal of the obstruction in the nasal airway significantly improve the breathing quality. However, the nasal airway experienced approximately about a 50 % decrease in total particle filtering efficiency after surgery. Therefore, careful consideration should be given to this matter before nasal operation especially for a patient with breathing allergic history. In the second part of this study, the morphology of the constricted pharyngeal representing OSA was found to significantly affect the airflow pattern and the deposition fraction of microparticles. The morphology of the upper airway, the size of the inhaled particle and breathing rate was found significantly affect the total particle deposition efficiency and local deposition fraction in the upper airway. The presented regional deposition fraction may be used in specifying the site of highest possibility for respiratory lesions according to the breathing rate and the size of the inhaled toxic particles. Results obtained from this study can be also used to estimate the location of airway obstruction in upper airway of patient with sleep apnea symptom. In the third part of this study, the surgical conducted procedure has cleared out the obstructions in the nasal airway hence improve the airflow distribution through the upper airway during inhalation process. This study shows that the nasal surgery alone can help improve the breathing quality in the upper airway with OSA. The reduction of the airflow resistance in the nasal cavity affect the pressure distribution in the lower part of the upper airway. Obstruction in the nasal passage and sudden airway expansion in the upper airway increased number of particles trap, recirculated and finally deposited in the airway. Finally, the experimental data obtained from the experimental study utilizing the developed pharyngeal airway further validate the result obtained from the numerical study.九州工業大学博士学位論文 学位記番号:生工博甲第315号 学位授与年月日:平成30年3月23日1: INTRODUCTION|2: LITERATURE REVIEW|3: MODELLING THE HUMAN UPPER AIRWAY|4: NUMERICAL SIMULATION METHODOLOGY|5: NUMERICAL INVESTIGATION ON AIRFLOW CHARACTERISTICS IN NASAL CAVITY HAVING TURBINATE HYPERTROPHY, CONCHA BULLOSA, AND SEPTUM DEVIATION WITH OSA: PRE- AND POST SURGERY|6: COMPUTATIONAL FLUID DYNAMICS STUDY OF AIRFLOW AND MICROPARTICLE DEPOSITION IN A CONSTRICTED PHARYNGEAL SECTION REPRESENTING OBSTRUCTIVE SLEEP APNEA DISEASE|7: NUMERICAL SIMULATION OF AIRFLOW AND AEROSOL DEPOSITION IN REALISTIC HUMAN UPPER AIRWAY WITH OBSTRUCTIVE SLEEP APNEA AND CHRONIC NASAL OBSTRUCTION: PRE- AND POST-SURGERY|8: EXPERIMENTAL INVESTIGATION|9: CONCLUSIONS AND FUTURE RECOMMENDATIONS九州工業大学平成29年

    Detection of severe obstructive sleep apnea through voice analysis

    Get PDF
    tThis paper deals with the potential and limitations of using voice and speech processing to detect Obstruc-tive Sleep Apnea (OSA). An extensive body of voice features has been extracted from patients whopresent various degrees of OSA as well as healthy controls. We analyse the utility of a reduced set offeatures for detecting OSA. We apply various feature selection and reduction schemes (statistical rank-ing, Genetic Algorithms, PCA, LDA) and compare various classifiers (Bayesian Classifiers, kNN, SupportVector Machines, neural networks, Adaboost). S-fold crossvalidation performed on 248 subjects showsthat in the extreme cases (that is, 127 controls and 121 patients with severe OSA) voice alone is able todiscriminate quite well between the presence and absence of OSA. However, this is not the case withmild OSA and healthy snoring patients where voice seems to play a secondary role. We found that thebest classification schemes are achieved using a Genetic Algorithm for feature selection/reduction

    Statistical Shape Modelling and Segmentation of the Respiratory Airway

    Get PDF
    The human respiratory airway consists of the upper (nasal cavity, pharynx) and the lower (trachea, bronchi) respiratory tracts. Accurate segmentation of these two airway tracts can lead to better diagnosis and interpretation of airway-specific diseases, and lead to improvement in the localization of abnormal metabolic or pathological sites found within and/or surrounding the respiratory regions. Due to the complexity and the variability displayed in the anatomical structure of the upper respiratory airway along with the challenges in distinguishing the nasal cavity from non-respiratory regions such as the paranasal sinuses, it is difficult for existing algorithms to accurately segment the upper airway without manual intervention. This thesis presents an implicit non-parametric framework for constructing a statistical shape model (SSM) of the upper and lower respiratory tract, capable of distinct shape generation and be adapted for segmentation. An SSM of the nasal cavity was successfully constructed using 50 nasal CT scans. The performance of the SSM was evaluated for compactness, specificity and generality. An averaged distance error of 1.47 mm was measured for the generality assessment. The constructed SSM was further adapted with a modified locally constrained random walk algorithm to segment the nasal cavity. The proposed algorithm was evaluated on 30 CT images and outperformed comparative state-of-the-art and conventional algorithms. For the lower airway, a separate algorithm was proposed to automatically segment the trachea and bronchi, and was designed to tolerate the image characteristics inherent in low-contrast CT images. The algorithm was evaluated on 20 clinical low-contrast CT from PET-CT patient studies and demonstrated better performance (87.1±2.8 DSC and distance error of 0.37±0.08 mm) in segmentation results against comparative state-of-the-art algorithms
    corecore