ArticleMedical & biological engineering & computing2022
Total hip replacement monitoring: numerical models for the acoustic emission technique.
Article in Medical & biological engineering & computing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- AI-Assisted 3D Planning of CT Parameters for Personalized Femoral Prosthesis Selection in Total Hip Arthroplasty.Therapeutics and clinical risk management · 2025Article
- Acoustic emission applied to stochastic modeling of microdamage in compact bone.Biomechanics and modeling in mechanobiology · 2024Article
- Surface Acoustic Wave (SAW) Sensors for Hip Implant: A Numerical and Computational Feasibility Investigation Using Finite Element Methods.Biosensors · 2023Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Any mechanical instability associated with total hip replacement (THR) excites elastic waves with different frequencies and propagates through the surrounding biological layers. Using the acoustic emission (AE) technique as a THR monitoring tool provides valuable information on structural degradations associated with these implants. However, several factors can compromise the reliability of the signals detected by AE sensors, such as attenuation of the detected signal due to the presence of biological layers in the human body between prosthesis (THR) and AE sensor. The main objective of this study is to develop a numerical model of THR that evaluates the impact of biological layer thicknesses on AE signal propagation. Adipose tissue thickness, which varies the most between patients, was modeled at two different thicknesses 40 mm and 70 mm, while the muscle and skin thicknesses were kept to a constant value. The proposed models were tested at different micromotions of 2 µm, 15-20 µm at modular junctions, and different frequencies of 10-60 kHz. Attenuation of signal is observed to be more with an increase in the selected boundary conditions along with an increase in distance the signals propagate through. Thereby, the numerical observations drawn on each interface helped to simulate the effect of tissue thicknesses and their impact on the attenuation of elastic wave propagation to the AE receiver sensor.
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Registered trials
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