Extracting guided wave characteristics of bone phantoms from ultrasonometric data for osteoporosis diagnosis

Глушков, Е. В.; Glushkova, Natalia; Ermolenko, Olga A.; Tatarinov, Alexey

doi:10.1109/dd55230.2022.9961013

Cited by 2 publications

(2 citation statements)

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“…In our studies, to extract wavenumbers from the measurement data, a modified MPM [ 40 ] is used with additional filtering by the H -function [ 41 ]. The objective function of the inverse problem is expressed in terms of the Green’s matrix elements calculated at the points of GW dispersion curves selected from the recorded signals.…”

Section: Introductionmentioning

confidence: 99%

“…The foundation of the present studies traces back to bone ultrasonometry research conducted in Riga starting in the 1980s [ 43 , 44 ]. In the 2000s, the research temporarily moved to Artann Laboratories, USA [ 7 , 45 ], and has since resumed in Riga [ 46 ], while the numerical analysis is carried out by the Krasnodar team [ 41 , 47 , 48 ].…”

Section: Introductionmentioning

confidence: 99%

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Study of Ultrasonic Guided Wave Propagation in Bone Composite Structures for Revealing Osteoporosis Diagnostic Indicators

Glushkov,

Glushkova,

Ermolenko

et al. 2023

Materials

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Tubular bones are layered waveguide structures composed of soft tissue, cortical and porous bone tissue, and bone marrow. Ultrasound diagnostics of such biocomposites are based on the guided wave excitation and registration by piezoelectric transducers applied to the waveguide surface. Meanwhile, the upper sublayers shield the diseased interior, creating difficulties in extracting information about its weakening from the surface signals. To overcome these difficulties, we exploit the advantages of the Green’s matrix-based approach and adopt the methods and algorithms developed for the guided wave structural health monitoring of industrial composites. Based on the computer models implementing this approach and experimental measurements performed on bone phantoms, we analyze the feasibility of using different wave characteristics to detect hidden diagnostic signs of developing osteoporosis. It is shown that, despite the poor excitability of the most useful modes associated with the diseased inner layers, the use of the improved matrix pencil method combined with objective functions based on the Green’s matrix allows for effective monitoring of changes in the elastic moduli of the deeper sublayers. We also note the sensitivity and monotonic dependence of the resonance response frequencies on the degradation of elastic properties, making them a promising indicator for osteoporosis diagnostics.

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Section: Introductionmentioning

confidence: 99%