Mechanical design, instrumentation and measurements from a hemoacoustic cardiac phantom

Bakhshaee, Hani; Garreau, Guillaume; Tognetti, Gaspar; Shoele, Kourosh; Carrero, Ronann; Kilmar, Thomas; Zhu, Chi; Thompson, William; Seo, Jong Hyun; Mittal, Rajat; Andreou, Andreas G.

doi:10.1109/ciss.2015.7086901

Cited by 6 publications

(5 citation statements)

References 6 publications

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“…Researchers have been striving to convert auscultation into a quantitative diagnostic tool since 1970s [3][4][5][6][7]. Moreover, due to the recent development of ultra-sensitive, low-cost, compact acoustic sensors, advanced signal processing tools and powerful portable computers, researchers have also been exploring the possibility of developing automated auscultation systems [8,9]. Such systems would reduce the subjectivity associated with human hearing acuity and training, making it suitable for rapid mass diagnostic screening, longitudinal (tracking over time) at-home monitoring of patient health, and field operations in areas with limited medical access.…”

Section: Introductionmentioning

confidence: 99%

Computational Modeling and Analysis of Murmurs Generated by Modeled Aortic Stenoses

Zhu

Seo

Mittal

2019

Journal of Biomechanical Engineering

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In this study, coupled hemodynamic–acoustic simulations are employed to study the generation and propagation of murmurs associated with aortic stenoses where the aorta with a stenosed aortic valve is modeled as a curved pipe with a constriction near the inlet. The hemodynamics of the poststenotic flow is investigated in detail in our previous numerical study (Zhu et al., 2018, “Computational Modelling and Analysis of Haemodynamics in a Simple Model of Aortic Stenosis,” J. Fluid Mech., 851, pp. 23–49). The temporal history of the pressure on the aortic lumen is recorded during the hemodynamic study and used as the murmur source in the acoustic simulations. The thorax is modeled as an elliptic cylinder and the thoracic tissue is assumed to be homogeneous, linear and viscoelastic. A previously developed high-order numerical method that is capable of dealing with immersed bodies is applied in the acoustic simulations. To mimic the clinical practice of auscultation, the sound signals from the epidermal surface are collected. The simulations show that the source of the aortic stenosis murmur is located at the proximal end of the aortic arch and that the sound intensity pattern on the epidermal surface can predict the source location of the murmurs reasonably well. Spectral analysis of the murmur reveals the disconnect between the break frequency obtained from the flow and from the murmur signal. Finally, it is also demonstrated that the source locations can also be predicted by solving an inverse problem using the free-space Green's function. The implications of these results for cardiac auscultation are discussed.

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Section: Introductionmentioning

confidence: 99%

Computational Modeling and Analysis of Murmurs Generated by Modeled Aortic Stenoses

Zhu

Seo

Mittal

2019

Journal of Biomechanical Engineering

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“…xÞhs j iðxÞ (10) where h i represents the Fourier transform of the function, and x is the angular frequency. The Green's function for the twodimensional problem has the following expression [31]:…”

Section: Verification Of Acoustic Modelingmentioning

confidence: 99%

“…Moreover, such a modality could be used for longitudinal tracking of patient health. For all these reasons, there is a renewed impetus to transform auscultation into a quantitative and accurate method [3,[7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

A Computational Method for Analyzing the Biomechanics of Arterial Bruits

Zhu

Seo

Bakhshaee

et al. 2017

Journal of Biomechanical Engineering

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A computational framework consisting of a one-way coupled hemodynamic-acoustic method and a wave-decomposition based postprocessing approach is developed to investigate the biomechanics of arterial bruits. This framework is then applied for studying the effect of the shear wave on the generation and propagation of bruits from a modeled stenosed artery. The blood flow in the artery is solved by an immersed boundary method (IBM) based incompressible flow solver. The sound generation and propagation in the blood volume are modeled by the linearized perturbed compressible equations, while the sound propagation through the surrounding tissue is modeled by the linear elastic wave equation. A decomposition method is employed to separate the acoustic signal into a compression/longitudinal component (curl free) and a shear/transverse component (divergence free), and the sound signals from cases with and without the shear modulus are monitored on the epidermal surface and are analyzed to reveal the influence of the shear wave. The results show that the compression wave dominates the detected sound signal in the immediate vicinity of the stenosis, whereas the shear wave has more influence on surface signals further downstream of the stenosis. The implications of these results on cardiac auscultation are discussed.

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“…Another clinical assessment technique that is safer and non-invasive is phonoangiography, which requires a computer-assisted device fitted with advanced sensors to identify bruits , i.e., changes in the sound of blood as it flows through a narrowed portion of an artery [15] . However, such investigations do not typically quantify the exact degree of stenosis but can classify it as mild, moderate, or severe (Azimpour et al [16] , Sun et al [17] , Duncan et al [18] , Bakhshaee et al [19] , Watrous et al [20] , Semmlow et al [21] ).…”

Section: Introductionmentioning

confidence: 99%

A 3D scaling law for supravalvular aortic stenosis suited for stethoscopic auscultations

Ali,

Ghobashy,

Sultan

et al. 2024

Heliyon

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Mechanical design, instrumentation and measurements from a hemoacoustic cardiac phantom

Cited by 6 publications

References 6 publications

Computational Modeling and Analysis of Murmurs Generated by Modeled Aortic Stenoses

Computational Modeling and Analysis of Murmurs Generated by Modeled Aortic Stenoses

A Computational Method for Analyzing the Biomechanics of Arterial Bruits

A 3D scaling law for supravalvular aortic stenosis suited for stethoscopic auscultations

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