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.

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 mm (compared to 98 mm 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.

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.

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.

Human motion has been analyzed for decades based on experimentally collected subject data, serving various purposes, from enhancing athletic performance to assisting patients' recovery in rehabilitation and many individuals can benefit significantly from study advancements. Human motion prediction, is a more challenging task because no experimental data are available in advance, particularly concerning repetitive tasks, such as box lifting and tossing, to prevent injury risks. Tossing, a common task in various industries, involves the simultaneous vertical and horizontal movement of objects but often results in bodily strain. This paper presents an optimization-based method for predicting two-dimensional (2D) symmetric tossing motion without relying on experimental data. The method employs sequential quadratic programming, which optimizes dynamic effort by incorporating both static and dynamic joint torque limits. To validate the proposed model, experimental data were collected from 10 subjects performing tossing tasks using a motion capture system and force plates. The predicted joint angles and ground reaction forces considering dynamic joint strength constraints were compared with their corresponding experimental data to validate the model. In addition, the predicted joint torques differences are compared between joint dynamics strengths and static strengths. The results showed that the predicted optimal tossing motions range between the maximum and minimum of the experimental standard deviation for kinematic data across all subjects and the ground reaction forces are also within the experimental data range. This supports the validity of the prediction model. The findings of this study could have practical applications, especially in preventing the potential risk of injuries among workers who have daily tossing jobs.

High-efficiency and high-quality sterilization technologies for medical materials can significantly reduce iatrogenic infection. This study investigates the synergistic effects of laser-induced periodic surface structures (LIPSS) and ultrasonic cleaning on the removal of bacteria from medical material surfaces. We specifically examined how ultrasonic parameters and structural defects in LIPSS impact the effectiveness of bacterial removal. As an emerging medical metal, Zr-BMG was chosen for the target material. Femtosecond laser processing was employed to create LIPSS with both complete linear arrays and discontinuous linear arrays structures featuring surface defects by adjusting the scanning overlap rate. A high-concentration solution of S. aureus was used for co-cultivation, resulting in a surface bacterial coverage rate exceeding 95%. The study analyzed the synergistic sterilization effect of microstructured surfaces through variations in ultrasonic cleaning power and duration. The results indicated that surfaces with microstructures demonstrated significantly improved bacterial removal following ultrasonic cleaning. The bacterial removal rate was found to be proportional to the ultrasonic vibrator power, and the surface with a LIPSS structure outperformed the discontinuous LIPSS surface in bacterial removal efficiency. Optimal results were achieved with the LIPSS surface after 30 min of cleaning at 100 W ultrasonic power. However, there was minimal difference in bacterial removal between 10 and 30 min at the same power level. This study aims to provide methodological insights and data support for the efficient and high-quality cleaning of medical metal surfaces.

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.

The purpose of this paper is to undertake a systematic review on various mechanical design considerations, simulation and optimization techniques as well as the clinical applications of energy storing and return (ESAR) prosthetic feet used in amputee rehabilitation. Methodological databases including PubMed, EMBASE, and SCOPUS were searched till July 2022, and the retrieved records were evaluated for relevance. The design, mechanism, materials used, mechanical and simulation techniques and clinical applications of ESAR foot used in developed and developing nations were reviewed. 61 articles met the inclusion criteria out of total 577 studies. A wide variety of design matrices for energy- storing feet was found, but the clinical relevance of its design parameters is uncommon. Definitive factors on technical and clinical characteristics were derived and included in the summary tables. To modify existing foot failure mechanisms, material selection and multiple experiments must be improved. Gait analysis and International Organization for Standardization (ISO) mechanical testing standards of energy-storing feet were the methods for integrating clinical experimentation with numerical results. To meet technological requirements, various frameworks simulate finite element models of the energy-storing foot, whereas clinical investigations involving gait analysis require proper insight. Analysis of structural behavior under varying loads and its effect on studies of functional gait are limited. For optimal functional performance, durability and affordability, more research and technological advancements are required to characterize materials and standardize prosthetic foot protocols.

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.

In this review, user experience (UX) of recent lower limb exoskeletons (LLEs) and its improvement methodologies are investigated. First, statistics based on standardised and custom UX evaluations are presented. It is indicated that, LLE users have positive UX, especially in the aspects of safety, dimension and effectiveness. Further, overall, UX levels of ankle and hip-knee exoskeletons are higher than those of other exoskeleton types; unilateral LLEs have higher mean UX levels than that of the bilateral ones. Then, design practices for improving UX are studied; the focused points are burden reduction and improvement of device fit. The former is achieved through lightweight design and approaches that reduce device's moment of inertia (MOI) at mechanical joints. Works on the latter refer to the endeavours to enhance static and dynamic fit; they mainly rely on the optimisations of human-robot interface (HRS) and endeavours to rectify misalignment of axes of mechanical and anatomic joints, respectively. The following section is control approaches to enhance wearing comfort level; it is mainly focused on adaptive, interaction and compensation-based controls. Finally, existing problems and future directions are stated and prospected respectively.

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.

This investigation attempts to propose a novel Wavelet and Local Binary Pattern-based Xception feature Descriptor (WLBPXD) framework, which uses a deep-learning model for classifying chronic infection amongst other infections. Chronic infection (COVID-19 in this study) is identified via RT-PCR test, which is time-consuming and requires a dedicated laboratory (materials, equipment, etc.) to complete the clinical results. X-rays and computed tomography images from chest scans offer an alternative method for identifying chronic infections. It has been demonstrated that chronic infection can be diagnosed from X-ray images acquired in a real-world setting. The images are transformed using the discrete wavelet transform (DWT), combined with the local binary pattern (LBP) technique. Pre-trained deep-learning models, such as AlexNet, Xception, VGG-16 and Inception Resnet50, extract the features. Subsequently, the extracted features are fused using feature-fusion approaches and subjected to classification. The AlexNet, in conjunction with the DWT model, produced 99.7% accurate results, whereas the AlexNet and the LBP model produced 99.6% accurate results. Therefore, the proposed method is efficient as it offers a better detection accuracy and eventually enhances the scope of early detection, thus assisting the clinical perspectives.

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.

Similar to how fiber orientation affects composite materials, osteon orientation affects the elasticity and fracture behavior of cortical bone. The objective of this work is to predict the combined effect of orientations of the osteon, applied load, and various crack lengths on the fracture characteristics of cortical bone. Orthotropic modeling and analyses of cortical bone were carried out using the linear-elastic fracture mechanics (LEFM) based extended finite element method (XFEM). Five values of applied mode-I and mode-II load, five distinct crack lengths, and seven angular osteon orientations were taken into consideration to predict the change in SIF. In this work, the 2-D plane stress assumption with a straight-edge crack was taken into consideration. It was found that the values of SIF significantly increased when the load (15-35 MPa) and fracture length (1.8-2.2 mm) increased. SIF () values under mode-I loading were discovered to be substantially lower than SIF ( and ) values under mode-II loading. Results of this study showed that osteon orientations with different crack lengths and applied loads had a significant impact on cortical bone fracture characteristics. Only the crack's opening was discovered to be caused by mode-I loading; however, both the opening and shearing of the crack were found to be caused by mode-II loading. Despite differences in applied loads, crack lengths, and osteon orientations, the values of the SIF predicted in this work (under mode-I loading) using LEFM-based XFEM exhibited good agreement with the prior published experimental and numerical data.

Using ultrasound technology as one of the therapeutic methods, in which ultrasound waves of different frequencies and intensities are employed, has significantly contributed to enhancing and facilitating the treatment process of various diseases. A Hemostatic Ultrasonic Scalpel can entail considerable advantages by simultaneously performing two operations tissue cutting and coagulation of biological tissues. In the present study, employing experimental design through response surface methodology, the effect of ultrasonic power and the duration of vibration application on the tissue has been investigated. Two parameters, namely the burst pressure of the sealed vessel and the length of the thermal seal zone, were measured by pressure testing and analysis image of the thermal effect region at the sealed vessel area, respectively. The pressure test results demonstrated that an input power of 52 W and the application of vibrations for 8 s under a constant force of 10 N, showed the optimized maximum burst pressure equal to 1100 mmHg. Examination of the sealed vessel images revealed a linear increase in thermal damage with increasing input power.

In many spine surgeries, pedicle screws are commonly used to stabilize vertebrae, however, loosening can be a complication. Different designs have shown improvements in fixation strength, with self-expandable screws featuring shape memory alloy (SMA) structures being of particular interest. This study aimed to assess the fixation strength of self-expandable pedicle screws made with SMA (specifically Nickel-Titanium) sheets. Three types of screws were evaluated: self-expandable screws with a smooth SMA surface, self-expandable screws with a porous SMA surface, and standard design screws. Each screw underwent pullout tests for comparison. Following the tests, the self-expandable screw with a porous surface exhibited the highest pullout force (1141.83 N), compared to 1056.86 N for the smooth self-expandable screw and 1104.25 N for the standard screw. The dissipated plastic strain energy differed among the screws, with values of 0.073 J for the porous self-expandable screw, 0.065 J for the smooth self-expandable screw, and 0.089 J for the standard pedicle screw. Notably, the porous self-expandable screw showed reduced stress on the bone-screw interface. Improving the mechanical design of pedicle screws could significantly enhance screw-bone fixation strength. The utilization of self-expandable pedicle screws with porous surface SMA sheets demonstrates superior performance, potentially mitigating complications like loosening.

As the natural conclusion of talent identification in sports, talent development is the process that involves improving biomechanical capacities and bio-motor abilities. The development progress can be objectively assessed and monitored through measurements of trainability. This study introduces a practical methodology to assess motor control as a trainable factor using kinematic data. The study focused on establishing the relationship between kinematic data and changes in muscle strength and dynamic balance. It illustrates how wearable technology can assess trainability during a functional training programme. Twenty-six female university students were selected and divided into intervention and control groups to investigate motor control trainability. The intervention group performed step aerobics exercises for 24 sessions. A single inertial measurement unit (IMU) mounted on S1 captured the oscillatory motion profiles of the centre of mass during these rhythmic exercises. Analysis revealed that the amplitude of linear jerk variability in different anatomical planes could reflect core and lower limb muscle strengthening caused by training. Furthermore, the results indicated that the dynamic balance adaptation to the changing tempo throughout the training programme was dictated primarily by step width. The mediolateral linear jerk variability reflected this adaptation. The minimum instrumentation approach proposed by this study could prove very practical for the talent development monitoring. The methodology illustrates how the recorded kinematic data from an appropriately placed single IMU could become an information-rich source for the coach to monitor, assess and quantify the trainee's progress during long-term athletic development.

Bulk metallic glasses (BMGs) have garnered significant attention in recent decades due to the outstanding physical, chemical, and biomedical characteristics. The biomedical application of metallic glass also received extensive attention. This report investigates the interplay among antibacterial performance, crystallization and processing parameters of Zr-based bulk metallic glass (Zr-BMG) following nanosecond laser irradiation. We examined surface morphology, crystallization behavior, surface quality, binding energy, and ion release properties post-laser irradiation. Additionally, we evaluated the generation of reactive oxygen species upon immersion of Zr-BMG in phosphate-buffered saline using the 2',7'-dichlorofluorescin diacetate method. Staphylococcus aureus was chosen to assess Zr-BMG's antibacterial performance, while mouse osteoblasts were utilized to investigate in vitro cytotoxicity. Our findings revealed that at laser energy intensities below 0.08 J/mm, the amorphous structure of Zr-BMG remained intact after irradiation. Moreover, laser irradiation significantly enhanced the antibacterial performance of Zr-BMG. The release rate of ion, concentration of reactive oxygen species, and antibacterial properties exhibited direct proportionality to laser energy intensity. However, surfaces exhibiting high antibacterial efficacy also displayed elevated cytotoxicity. The surface irradiated with a 7 μJ ablation pulse and 200 mm/s irradiation speed demonstrated a superior balance between antibacterial and cytotoxic properties while maintaining an amorphous state. We hope this research can provide theoretical reference and data support for the application of metallic glass in biomedical application.

Polyether-ether-ketone (PEEK) has been widely applied in various fields due to its excellent mechanical properties and biocompatibility. The efficient and high-quality customized manufacturing of PEEK components are investigated in this study by the hybrid 3D printing and milling process. At first, the alternating hybrid process is selected and verified by comparing two typical hybrid process categories and conducting experiments, respectively. Second, a set of procedures are designed to automate the engineering application of the hybrid process trying to avoid the disadvantages of manual programing. Then, considering the tool length and possible interferences during the hybrid process, a model segmentation algorithm, namely, the exchange principle of avoiding interference (EPAI) is proposed. Based on the introduced EPAI and the programing language Python, the additive and subtractive hybrid manufacturing (ASHM) data processing procedure is proposed and realized by post-processing of the conventional 3D printing codes. Finally, the feasibility experiments have been conducted. The experimental results verify the hybrid manufacturing process in the fabrication of parts with complex internal features. The surface roughness and dimensional error of the parts have been reduced by 75.5% and 85.2%, respectively, while the shear strength has been increased by 14.1%. Compared with conventional milling process, the material consumption is reduced by 48.7%.

Additive Manufacturing (AM) encompasses various techniques creating intricate components from digital models. The aim of incorporating 3D printing (3DP) in the healthcare sector is to transform patient care by providing personalized solutions, improving medical procedures, fostering research and development, and ultimately optimizing the efficiency and effectiveness of healthcare delivery. This review delves into the historical beginnings of AM's 9 integration into medical contexts exploring various categories of AM methodologies and their roles within the medical sector. This survey also dives into the issue of material requirements and challenges specific to AM's medical applications. Emphasis is placed on how AM processes directly enhance human well-being. The primary focus of this paper is to highlight the evolution and incentives for cross-disciplinary AM applications, particularly in the realm of healthcare by considering their principle, materials and applications. It is designed for a diverse audience, including manufacturing professionals and researchers, seeking insights into this transformative technology's medical dimensions.

Bone ingrowth into a porous implant is necessary for its long-term fixation. Although attempts have been made to quantify the peri-implant bone growth using finite element (FE) analysis integrated with mechanoregulatory algorithms, bone ingrowth into a porous cellular hip stem has scarcely been investigated. Using a three-dimensional (3D) FE model and mechanobiology-based numerical framework, the objective of this study was to predict the spatial distribution of evolutionary bone ingrowth into an uncemented novel porous hip stem proposed earlier by the authors. A CT-based FE macromodel of the implant-bone structure was developed. The bone material properties were assigned based on CT grey value. Peak musculoskeletal loading conditions, corresponding to level walking and stair climbing, were applied. The geometry of the implant-bone macromodel was divided into multiple submodels. A suitable mapping framework was used to transfer maximum nodal displacements from the FE macromodel to the cut boundaries of the FE submodels. CT grey value-based bone materials properties were assigned to the submodels. Thereafter, the submodels were solved and simulations of bone ingrowth were carried out using mechanoregulatory principle. A gradual increase in the average Young's modulus, from 1200 to 1500 MPa, of the bone tissue layer was observed considering all the submodels. The distal submodel exhibited 82% of bone ingrowth, whereas the proximal submodel experienced 65% bone ingrowth. Equilibrium in the bone ingrowth process was achieved in 7 weeks postoperatively, with a notable amount of bone ingrowth that should lead to biological fixation of the novel hip stem.