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Erschienen in: Medical & Biological Engineering & Computing 8/2019

08.06.2019 | Original Article

Experimental and numerical investigation on soft tissue dynamic response due to turbulence-induced arterial vibration

verfasst von: Huseyin Enes Salman, Yigit Yazicioglu

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 8/2019

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Abstract

Peripheral arterial occlusive disease is a serious cardiovascular disorder. The arterial occlusion leads to turbulent flow and arterial sound generation on the inner vessel wall. Stenosis-induced vibro-acoustic waves propagate through the surrounding soft tissues and reach the skin surface. In this study, the feasibility of noninvasive acoustic detection of the peripheral arterial stenosis is investigated using the vibration responses by means of experimental and computational models. Latex rubber tube is used to model the artery, and it is surrounded by a tissue mimicking phantom made of bovine gelatin. Vibration responses on phantom surface are measured using laser Doppler vibrometer, and computational results are obtained performing modal analysis. Experimental findings and computational results showed well agreement in terms of spectral content and vibration amplitudes. The effects of various stenosis severities, flow rates, and phantom thicknesses on the vibration responses are investigated from diagnostic perspective. Stenosis severities greater than 70% resulted in a considerable increase in vibration amplitudes. The structural mode shapes of the tissue phantom are dominant between 0 and 100 Hz, suppressing the signals generated by the stenosis. The optimum range of frequency for acoustic stenosis detection is concluded to be between 200 and 500 Hz, particularly around 300 Hz.

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Metadaten
Titel
Experimental and numerical investigation on soft tissue dynamic response due to turbulence-induced arterial vibration
verfasst von
Huseyin Enes Salman
Yigit Yazicioglu
Publikationsdatum
08.06.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Medical & Biological Engineering & Computing / Ausgabe 8/2019
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-019-01995-y

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