physiologic model
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2019 ◽  
Vol 130 (2) ◽  
pp. 309-313
Author(s):  
Ryan S. Ference ◽  
James A. Leonard ◽  
Howard D. Stupak

2019 ◽  
Vol 62 (2) ◽  
pp. 215-228
Author(s):  
Daniel J. Croake ◽  
Richard D. Andreatta ◽  
Joseph C. Stemple

Purpose Normative data for many objective voice measures are routinely used in clinical voice assessment; however, normative data reflect vocal output, but not vocalization process. The underlying physiologic processes of healthy phonation have been shown to be nonlinear and thus are likely different across individuals. Dynamic systems theory postulates that performance behaviors emerge from the nonlinear interplay of multiple physiologic components and that certain patterns are preferred and loosely governed by the interactions of physiology, task, and environment. The purpose of this study was to descriptively characterize the interactive nature of the vocalization subsystem triad in subjects with healthy voices and to determine if differing subgroups could be delineated to better understand how healthy voicing is physiologically generated. Method Respiratory kinematic, aerodynamic, and acoustic formant data were obtained from 29 individuals with healthy voices (21 female and eight male). Multivariate analyses were used to descriptively characterize the interactions among the subsystems that contributed to healthy voicing. Results Group data revealed representative measures of the 3 subsystems to be generally within the boundaries of established normative data. Despite this, 3 distinct clusters were delineated that represented 3 subgroups of individuals with differing subsystem patterning. Seven of the 9 measured variables in this study were found to be significantly different across at least 1 of the 3 subgroups indicating differing physiologic processes across individuals. Conclusion Vocal output in healthy individuals appears to be generated by distinct and preferred physiologic processes that were represented by 3 subgroups indicating that the process of vocalization is different among individuals, but not entirely idiosyncratic. Possibilities for these differences are explored using the framework of dynamic systems theory and the dynamics of emergent behaviors. A revised physiologic model of phonation that accounts for differences within and among the vocalization subsystems is described. Supplemental Material https://doi.org/10.23641/asha.7616462


2018 ◽  
Vol 6 (3) ◽  
pp. 138-145 ◽  
Author(s):  
Gianluca Rigatelli ◽  
Marco Zuin ◽  
Fabio Dell’Avvocata ◽  
Aravinda Nanjundappa ◽  
Ramesh Daggubati ◽  
...  

Abstract Objectives To non-invasively evaluate by computational fluid dynamic (CFD) analysis the physiology and rheology of aortoiliac bifurcation disease at different angles and different stent configurations. Material and methods For the analysis, we considered a physiologic model of abdominal aorta with an iliac bifurcation set at 30°, 45° and 70° without stenosis. Subsequently, a bilateral ostial common iliac stenosis of 80% was considered for each type of bifurcation. For the stent simulation, we reconstructed Zilver vascular self-expanding (Zilver; Cook, Bloomington, MN) and Palmaz Genesis Peripheral (Cordis, Miami, FL) stents. Results The physiologic model, across the different angles, static pressure, Reynolds number and stream function, were lower for the 30° bifurcation angle with a gradient from 70° to 30° angles, whereas all the other parameters were inversely higher. After stenting, all the fluid parameters decreased homogenously independent of the stent type, maintaining a gradient in favour of 30° compared to 45° and 70° angles. The absolute greater deviation from physiology was observed for low kissing when self-expandable stents were used across all angles; in particular, the wall shear stress was high at at 45° angle. Conclusion Bifurcation angle deeply impacts the physiology of aortoiliac bifurcations, which are used to predict the fluid dynamic profile after stenting. CFD, having the potential to be derived both from computed tomography scan or invasive angiography, appears to be an ideal tool to predict fluid dynamic profile before and after stenting in aortoiliac bifurcation.


2018 ◽  
Vol 46 (7) ◽  
pp. e642-e648 ◽  
Author(s):  
Dan Stieper Karbing ◽  
Savino Spadaro ◽  
Nilanjan Dey ◽  
Riccardo Ragazzi ◽  
Elisabetta Marangoni ◽  
...  

2018 ◽  
Vol 126 (1) ◽  
pp. 93-101 ◽  
Author(s):  
Charles R. Sims ◽  
Luis R. Delima ◽  
Arthur Calimaran ◽  
Robert Hester ◽  
W. Andrew Pruett

2017 ◽  
Vol 216 (1) ◽  
pp. S194
Author(s):  
Avinash Patil ◽  
Lindsay Maggio ◽  
Sarah Dotters-Katz ◽  
Tracy Manuck ◽  
Ravi Gunatilake ◽  
...  
Keyword(s):  

2015 ◽  
Vol 74 ◽  
pp. 86-94 ◽  
Author(s):  
Ana Cuesta-Gragera ◽  
Carmen Navarro-Fontestad ◽  
Victor Mangas-Sanjuan ◽  
Isabel González-Álvarez ◽  
Alfredo García-Arieta ◽  
...  

2014 ◽  
Vol 28 (S1) ◽  
Author(s):  
William Huckle ◽  
Galit Frydman ◽  
Cassandra Martin ◽  
Shaneke Weerakoon ◽  
Kristobal Gudenschwager

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
Dinesh A. Peter ◽  
Yared Alemu ◽  
Michalis Xenos ◽  
Ori Weisberg ◽  
Itzhak Avneri ◽  
...  

Drug-resistant hypertensive patients may be treated by mechanical stimulation of stretch-sensitive baroreceptors located in the sinus of carotid arteries. To evaluate the efficacy of endovascular devices to stretch the carotid sinus such that the induced strain might trigger baroreceptors to increase action potential firing rate and thereby reduce systemic blood pressure, numerical simulations were conducted of devices deployed in subject-specific carotid models. Two models were chosen—a typical physiologic carotid and a diminutive atypical physiologic model representing a clinically worst case scenario—to evaluate the effects of device deployment in normal and extreme cases, respectively. Based on the anatomical dimensions of the carotids, two different device sizes were chosen out of five total device sizes available. A fluid structure interaction (FSI) simulation methodology with contact surface between the device and the arterial wall was implemented for resolving the stresses and strains induced by device deployment. Results indicate that device deployment in the carotid sinus of the physiologic model induces an increase of 2.5% and 7.5% in circumferential and longitudinal wall stretch, respectively, and a maximum of 54% increase in von Mises arterial stress at the sinus wall baroreceptor region. The second device, deployed in the diminutive carotid model, induces an increase of 6% in both circumferential and longitudinal stretch and a 50% maximum increase in von Mises stress at the sinus wall baroreceptor region. Device deployment has a minimal effect on blood-flow patterns, indicating that it does not adversely affect carotid bifurcation hemodynamics in the physiologic model. In the smaller carotid model, deployment of the device lowers wall shear stress at sinus by 16% while accelerating flow entering the external carotid artery branch. Our FSI simulations of carotid arteries with deployed device show that the device induces localized increase in wall stretch at the sinus, suggesting that this will activate baroreceptors and subsequently may control hypertension in drug-resistant hypertensive patients, with no consequential deleterious effects on the carotid sinus hemodynamics.


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