Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine最新文献

The use of ultrasound contrast agents (UCAs) for estimating portal pressure has recently gained attention due to its clinical promise, yet variability in acoustic amplitude poses challenges. UCAs contain microbubbles (1-10 µm in diameter), and understanding their acoustic response is essential to address this variability. However, systematic exploration of factors influencing microbubble behavior remains limited in current literature. This paper introduces a novel finite element analysis-based framework for portal pressure estimation, bridging key gaps. Developed in two stages, the model first captures the subharmonic response of a single bubble to an acoustic excitation of 50 kPa at 4 MHz, highlighting the influence of bubble size on resonance frequency. In the second stage, single-bubble responses are extended to analyze how microbubble population, size, and spatial distribution affect portal pressure estimation. For the first time, this study elucidates the experimental scatter in pressure measurements through a comprehensive consideration of these variables, offering new directions for UCA-based clinical pressure estimation in applications such as portal and cardiac pressure assessment.

Assessing the kinematics of the upper limbs is crucial for rehabilitation treatment, especially for stroke survivors. Nowadays, researchers use computer vision-based algorithms for Human motion analysis. However, specific challenges include less accuracy, increased computational complexity and a limited number of anatomical key points. This study aims to develop a novel algorithm using the MediaPipe framework to estimate five specific upper limb movements in stroke survivors. A single mobile camera recorded the movements on their affected side in a study involving 10 hemiplegic patients. The algorithm was then utilized to calculate the angles associated with each movement, and its accuracy was validated against standard goniometer readings, showing a mean bias within an acceptable range. Additionally, a Bland-Altman analysis demonstrated a 95% limit of agreement between the algorithm's results and those of the Goniometer, indicating reliable performance. The MediaPipe framework provides several advantages over other methods like OpenPose and PoseNet, such as several anatomical key points, improved precision and reduced execution time. This algorithm facilitates efficient measurement of upper limb movement angles in stroke survivors and allows for straightforward tracking of mobility improvements. Such innovative technology is a valuable tool for healthcare professionals assessing upper limb kinematics in rehabilitation settings.

The DePuy ASR hip implant systems had exceptionally high Cumulative Percent Revision compared with other implants in Australia. This was likely to be the case worldwide and thus the ASR hip implant systems were voluntarily withdrawn by DePuy on August 24, 2010. To avoid such debacles in future implant systems, it is instructive for biotribologists to examine the warnings provided by hip wear simulator testing prior to market release circa 2004. The ASR hip implants had metal-on-metal bearings that had shown some success in other designs. Based on hip wear simulator studies of these designs (mostly having 28 mm diameter heads), a Safe Zone for Wear Rates versus Implantation Time could be defined. However, some of the earlier metal-on-metal designs were wear simulator tested under some harsher clinically relevant conditions. They missed the Safe Zone thus confirming a biotribological risk for ASR hip implant systems. Subsequent analysis after market release of the ASR implants confirmed that the risk had been underestimated. Biotribological risk for new implant designs should be examined rigorously prior to market release.

This paper creates 3D models of Kitchon Root Controlled Auxiliary Archwire (Kitchon-RCAA) with different material properties and assembles them onto the main archwire equipped with brackets. By setting different loading methods and conducting Finite Element Analysis (FEA), the range of Orthodontic Torque/Support Force (OT/SF) values can be obtained. From the obtained values, it can be seen that changes in material properties have a significant impact on the mechanical properties of Kitchon-RCAA. When the properties of the Kitchon-RCAA material change two or more times, the mechanical values generated by Kitchon-RCAA cannot be directly added from two or more separate changes in the properties of the material. Therefore, it is necessary to simulate the model after each parameter change to obtain new results. And then the maxillary bio-model is reconstructed in reverse based on Cone Beam Computerized Tomography (CBCT) images. The biomechanical data equivalent to the mechanical mechanics generated by the root control assisted archwire is also added to the corresponding tooth positions, making indirect orthodontic behavior of Kitchon-RCAA on teeth possible. From the obtained results, it can be seen that the von Mises stress and total deformation magnitude for both normal teeth and corresponding Periodontal Ligament (PDL) position show a stable trend, while the Right Cuspid (R-C) and corresponding PDL with malformed root have a large stress concentration and may have a mold penetration problem. Overall, this paper not only analyses the mechanical behavior of the Kitchon-RCAA, this article not only analyzed the mechanical behavior of Kitchon-RCAA, but also its effect on the indirect biomechanical behavior of the teeth and PDL. And in combination with simulation result nephograms, it also enables predictability and visualization of orthodontic results. This helps dentists to provide safer and more reliable individualized orthodontic treatment plans for patients.

Bone is a highly heterogeneous and anisotropic material with a hierarchical structure. The effect of diaphysis locations and directions of loading on elastic-plastic compressive properties of bovine femoral cortical bone was examined in this study. The impact of location and loading directions on elastic-plastic compressive properties of cortical bone was found to be statistically insignificant in this study. The variances of most of the compressive properties were also observed to be location and directionality independent except for the locational differences in modulus of resilience (distal to central for longitudinal loading) and plastic work (central to distal for transverse loading) as well as differences in variances of the modulus of resilience and elastic modulus values for two directions of loading. The micro-mechanisms of cortical bone failure for longitudinal and transverse directions of loading were considered to be responsible for the difference in variances in the later properties values as well as for the maximum and minimum coefficient of variation (CV) obtained for compressive properties in two directions of loading. The representative cubical volume at the tested hierarchical level contained all unique microstructural features of the plexiform bone and therefore produced the homogeneous and isotropic elastic-plastic compressive properties of cortical bone. It is expected that the outcome of this study may be helpful in the area of bone tissue engineering and finite element simulation of cortical bone.

Subject-specific finite element models of knee joint contact mechanics are used in assessment of interventions and disease states. Cartilage thickness distribution is one factor influencing the distribution of pressure. Precision of cartilage geometry capture varies between imaging protocols. This work evaluated the cartilage thickness distribution precision needed for contact mechanics prediction in models of the tibiofemoral joint by comparing model outputs to experimental measurements for three cadaveric specimens. Models with location-specific cartilage thickness were compared to those with a uniform thickness, for a fixed relative orientation of the femur and tibia and with tibial freedom of movement. Under constrained conditions, the advantage of including location-specific cartilage thickness was clear. Models with location-specific thickness predicted the proportion of force through each condyle with an average error of 5% (compared to 27% with uniform thickness) and predicted the experimental contact area with an error of 21 mm² (compared to 98 mm² with uniform thickness). With tibial freedom, the advantage of location-specific cartilage thickness not clear. The attempt to allow three degrees of relative freedom at the tibiofemoral joint resulted in a high degree of experimental and computational uncertainty. It is therefore recommended that researchers avoid this level of freedom. This work provides some evidence that highly constrained conditions make tibiofemoral contact mechanics predictions more sensitive to cartilage thickness and should perhaps be avoided in studies where the means to generate subject-specific cartilage thickness are not available.

Repair and regeneration of damaged tissues due to disease and accidents have become a severe challenge to tissue engineers and researchers. In recent years, biocompatible metal materials such as stainless steels, cobalt alloys, titanium alloys, tantalum alloys, nitinol, and Mg alloys have been studied for tissue engineering applications; as suitable candidates in orthopedic and dentistry implants. These materials and their alloys are used for load-bearing and physiological roles in biological applications. Due to the suitable conditions provided by a porous material, many studies have been performed on the porous implants, including Mg-based scaffolds. Mg alloy scaffolds are attractive due to some outstanding features and susceptibilities, such as providing a cell matrix for cell proliferation, migration, and regeneration, providing metabolic substances for bone tissue growth, biocompatibility, good biodegradability, elastic modulus comparable to the natural bone, etc. Accordingly, in the present study, a general classification of all the production methods of Mg-based scaffolds is provided. Strengths and weaknesses, the effect of the production approach on the final properties of scaffolds, including mechanical and biological capabilities, and the impact of alloying elements and process parameters have been reviewed, and discussed. Finally, the manufacturing methods have been compared and the upcoming challenges have been stated.

During the robotic grinding of vertebral plates in high-risk laminectomy procedures, programmed operations may inadvertently induce force or temperature-related damage to the bone tissue. Therefore, it is imperative to explore a control methodology aimed at minimizing such damage during the robotic grinding of vertebral plate cortical bone, contingent upon optimal grinding parameters. Initially, predictive models for both the grinding force and temperature of vertebral plate cortical bone were developed using the response surface design (RSD) methodology. Subsequently, employing the satisfaction function approach, multi-objective parameter optimization of these predictive models was conducted to ascertain the optimal combination of parameters conducive to low-damage grinding. The optimum grinding parameters identified were a speed of 6000 r/min, a depth of grind of 0.4 mm, and a feed rate of 3.8 mm/s. Moreover, a multi-layer adaptive fuzzy control strategy was devised, and a corresponding multi-layer adaptive fuzzy controller (MFLC) was then implemented to dynamically adjust the grinding feed speed. The efficacy of this control module was corroborated through Simulink simulations. Simulation results demonstrated that the magnitude of the grinding force fluctuated within the range of 2.2-2.6 N after FLC control, while the fluctuation range of the grinding force was limited to 2.2-2.48 N after MFLC control. This indicates that MFLC control brings the force closer to the target expectation value of 2.39 N compared with FLC control. Finally, the dynamic fuzzy control method predicated on optimal grinding parameters was validated through experimental porcine spine grinding conducted on a robotic vertebral plate grinding platform.

Arterial stiffness has emerged as a prominent marker of risk for cardiovascular diseases. Few studies are interested in predicting symptomatic or asymptomatic arterial stiffness from hemodynamics and biomechanics parameters. Machine learning models can be used as an intelligent tool for arterial stiffness detection based on hemodynamic and biomechanical parameters. Indeed, in the case of arterial stiffness hemodynamics and biomechanics parameters present significant change, such as an increase in age, local wave velocity, arterial elastance, Young's modulus, reflected wave amplitude, decrease in arterial compliance, reflected wave arrival time, and reflection coefficient. This study aims to assess the impact of artificial intelligence using machine-learning algorithms for the detection of arterial stiffness. The ability of various machine-learning approaches can be investigated to predict wall stiffness in the carotid artery and to evaluate the risk of cardiovascular events. A mathematical model developed in previous work was used to determine hemodynamic and biomechanical parameters. Accuracy, sensitivity, and specificity are calculated to evaluate the performance of the proposed models. All used classifiers demonstrated high performance in predicting arterial stiffness, notably with the Support Vector Machine, Artificial Neural Network, and Decision Tree classifiers achieving exceptional accuracies of 100%. In this study, the potential of machine learning based on hemodynamic parameters for the prediction of symptomatic and asymptomatic arterial stiffness was demonstrated.