Search Results (313)

Previous models of extraocular mechanics have often assumed isotropic properties for ocular tissues, despite evidence indicating anisotropy in the optic nerve sheath (ONS). To investigate this further, we developed a finite element model (FEM) of horizontal eye rotation using MRI data from a living subject with normal tension glaucoma. Mechanical properties were derived from tensile tests on 17 post-mortem human eyes, revealing previously unrecognized anisotropic characteristics in the ONS. We simulated ±32° horizontal eye rotations and compared isotropic versus anisotropic ONS properties using the Holzapfel model. Strain distributions in the optic nerve (ON) were analyzed using ABAQUS 2024 software. During 32° adduction, stress and strain were concentrated at the ONS-sclera junction, reaching 8 MPa and 40% with isotropic properties, and 15 MPa and 30% with anisotropic properties. In contrast, during 32° abduction, stress was lower and strain was higher in the isotropic case (6 MPa and 30%) compared to the anisotropic case (12 MPa and 25%). Increased intraocular and intracranial pressures had minimal impact on the mechanical responses. These findings suggest that the anisotropic properties of the ONS increase stress concentration at the optic disc while reducing strain during eye movements, offering new insights into ocular biomechanics. A novel phenomenon emerged from the simulations: during larger ductions, the peripapillary Bruch’s membrane is predicted to wrinkle, forming undulations with an approximately 20 μm amplitude and 100 μm wavelength at its interface with the retina and choroid. Full article

Purpose: Pickleball, the fastest-growing sport in the United States, has seen a rapid increase in participation across all age groups, particularly among older adults. However, the sport introduces specific risks for ocular injuries due to the unique dynamics of gameplay and the physical properties of the pickleball. This study aims to explore the mechanisms of pickleball-related eye injuries, utilizing finite element modeling (FEM) to simulate ocular trauma and better understand injury mechanisms. Methods: A multi-modal approach was employed to investigate pickleball-related ocular injuries. Finite element modeling (FEM) was used to simulate blunt trauma to the eye caused by a pickleball. The FEM incorporated detailed anatomical models of the periorbital structures, cornea, sclera, and vitreous body, using hyperelastic material properties derived from experimental data. The simulations evaluated various impact scenarios, including changes in ball velocity, angle of impact, and material stiffness, to determine the stress distribution, peak strain, and deformation in ocular structures. The FEM outputs were correlated with clinical findings to validate the injury mechanisms. Results: The FE analysis revealed that the rigid, hard-plastic construction of a pickleball results in concentrated stress and strain transfer to ocular structures upon impact. At velocities exceeding 30 mph, simulations showed significant corneal deformation, with peak stresses localized at the limbus and anterior sclera. Moreover, our results show a significant stress applied to lens zonules (as high as 0.35 MPa), leading to potential lens dislocation. Posterior segment deformation was also observed, with high strain levels in the retina and vitreous, consistent with clinical observations of retinal tears and vitreous hemorrhage. Validation against reported injuries confirmed the model’s accuracy in predicting both mild injuries (e.g., corneal abrasions) and severe outcomes (e.g., hyphema, globe rupture). Conclusions: Finite element analysis provides critical insights into the biomechanical mechanisms underlying pickleball-related ocular injuries. The findings underscore the need for preventive measures, particularly among older adults, who exhibit age-related vulnerabilities. Education on the importance of wearing protective eyewear and optimizing game rules to minimize high-risk scenarios, such as close-range volleys, is essential. Further refinement of the FEM, including parametric studies and integration of protective eyewear, can guide the development of safety standards and reduce the socio-economic burden of these injuries. Full article

Upper molar distalization using clear aligners requires optimal force direction and control to ensure effective and predictable tooth movement. This study aimed to evaluate the biomechanical effects of different aligner trimline lengths (trimline ending at the gingival margin vs. 2 mm extended) and attachment designs (no attachment, vertical rectangular, 25-degree beveled vertical, and double horizontal) on maxillary first molar distalization using finite element analysis. A three-dimensional maxillary model was constructed from CBCT data, and eight different aligner configurations were simulated under identical distalizing force. The stress distribution within the periodontal ligament of the maxillary first molar and displacement of crown and root landmarks in three axes were analyzed. The models with no attachments and trimlines ending at the gingival margin exhibited the highest degree of uncontrolled tipping and uneven stress distribution. In contrast, models combining extended trimlines with either beveled vertical or double horizontal attachments demonstrated more controlled bodily movement, reduced palatal root mesial displacement, and more uniform vertical movement. Overall, extended trimlines were associated with increased total distalization and improved force transmission. These findings provide biomechanical insight into optimizing aligner configuration for upper molar distalization and may guide clinicians and manufacturers in improving treatment precision and predictability. Full article

This research focuses on the crucial issue of ascertaining safe and suitable massage forces for abdominal massage robots. It does so by constructing variable stiffness soft tissue physical models and devising a machine learning-based prediction algorithm. Twelve healthy volunteers with diverse body types (underweight, standard, overweight) were enlisted. A self-developed experimental platform was utilized to gather high-precision mechanical data. Two physical models were formulated to depict the nonlinear force-displacement relationship of abdominal soft tissues. Model 1 was based on an exponential function, and Model 2 was based on a power function. Model 1 showed greater accuracy for standard body types (R² > 0.95 at 72.22% of data points) and underweight body types (R² > 0.95 at 100% of data points). In contrast, Model 2 was a better fit for overweight individuals (R² > 0.95 at 47.06% of data points). Furthermore, a transformer-based machine learning algorithm was developed. This algorithm predicts interaction forces using anthropometric and physiological characteristics. It achieved an accuracy of 92.60% within a pressing depth of 0–15 mm. In most situations, especially in full-range predictions (with an accuracy of 58.60%), the algorithm outperformed both physical models. This study presents a dual framework that combines biomechanical modeling and data-driven algorithms. It lays the theoretical and practical groundwork for safe and adaptable force control in abdominal massage robotics. Full article

Background: Bone elasticity is one of the most important biomechanical parameters of the skeleton. It varies markedly with age, anatomical zone, bone type (cortical or trabecular) and bone marrow status. Methods: This review presents the result of a systematic review and analysis of 495 experimental and analytical papers on the elastic properties of bone tissue. The bone characteristics of hip, shoulder, skull, vertebrae as a function of the factors of age (young and old), sex (male and female), presence/absence of bone marrow and different test methods are examined. The Bayesian neural network (BNN) was used to estimate the uncertainty in some skeletal parameters (age, sex, and body mass index) in predicting bone elastic modulus. Results: It was found that the modulus of elasticity of cortical bone in young people is in the range of 10–30 GPa (depending on the type of bone), and with increasing age, this slightly decreases to 10–25 GPa, while trabecular tissue varies from 0.2 to 5 GPa and reacts more acutely to osteoporosis. Bone marrow, according to several studies, is able to partially increase stiffness under impact loading, but its contribution is minimal under slow deformations. Conclusions: BNN confirmed high variability, supplementing the predictions with confidence intervals and allowed the formation of equations for the calculation of bone tissue elastic modulus for the subsequent selection of the recommended elastic modulus of the finished implant, taking into account the biomechanical characteristics of bone tissue depending on age (young and old), sex (men and women) and anatomical zones of the human skeleton. Full article

Background: The role of the periarticular muscles of the knee joint in ensuring body balance is still ambiguous. Therefore, we conducted clinical and biomechanical assessments on 52 older adults (36 women and 16 men, age of 67.58 ± 7.30 years, body weight of 75.10 ± 13.42 kg, and height of 163.92 ± 8.80 cm) to determine the role of the knee muscles in balance maintenance. Methods: The clinical examination included the Dizziness Handicap Inventory (DHI), the Geriatric Depression Scale (GDS), the Performance-Oriented Mobility Assessment (POMA), the Functional Reach Test (FRT), the Falls Efficacy Scale—International (FES-I), and bioimpedance parameters (skeletal muscle mass—SMM—and its derived parameter—Diff SMM). The biomechanical assessment involved parameters that characterize muscle torques of knee joint extensors and flexors in isokinetic and isometric conditions, as well as changes in the centre of pressure (COP) position while standing with eyes open and closed. Results: Based on treatment history and DHI results (>10 points), 26 participants were identified as having balance disorders, while the remaining participants formed the control group. Statistical analysis was performed to determine differences between the groups. The groups significantly differed in terms of the results obtained from the DHI (p < 0.001) and GDS (p = 0.04) questionnaires as well as FES-I (p < 0.001) and POMA (p = 0.002) tests. While SMM (p = 0.012) was similar in the groups, Diff SMM (p = 0.04) significantly differed. The multiple regression analysis confirmed the knee joint extensor parameters’ significant role in predicting the COP path (p = 0.03 and p = 0.04 for two assumed models). Conclusions: The obtained results proved that the muscle torques of knee extensors can be used in the diagnostic process of older patients with balance disorders, indicating possible rehabilitation directions. Full article

(1) Background: Dynamic knee valgus (DKV) is a common biomechanical risk factor for knee injuries, particularly in sports involving high-intensity movements, such as basketball. While neuromuscular control and structural alignment contribute to DKV, recent evidence indicates that lower limb muscle power (LLMP) and cardiorespiratory fitness (CRF) may significantly influence DKV. This study aims to examine the relationship among LLMP, CRF, and DKV in adolescent basketball athletes. (2) Methods: A total of 104 adolescent basketball athletes (63.5% boys), 12 to 17 years old (13.87 ± 1.46 years) participated in this study. Anthropometric and demographic characteristics such as sex, age, height, weight, and body mass index (BMI) were recorded. The Counter Movement Jump (CMJ) was used for the evaluation and prediction of the LLMP, the 20 m shuttle run test (20mSRT) was used for the evaluation and prediction of CRF, and the single-leg drop jump (SLDJ) was used for the evaluation of DKV via a two-dimensional (2D) kinematic analysis. Statistical analysis included Pearson and Spearman correlations, as well as multiple linear regression, to determine the relationship among LLMP, CRF, and DKV. (3) Results: A statistical analysis revealed strong correlations among LLMP, CRF, and DKV. Pearson’s correlation coefficients demonstrated significant associations between the VO₂max and frontal plane projection angle (FPPA) (r = 0.78, p < 0.001), as well as between LLMP and FPPA (r = 0.82, p < 0.001). Multiple linear regression analysis showed that VO₂max and LLMP together accounted for 85% of the variance in FPPA (R² = 0.85, p < 0.001). (4) Conclusions: The findings highlight that both aerobic capacity and lower limb muscle power significantly contribute to knee valgus control among adolescent basketball players. Implementing training programs focused on improving lower limb muscle power and cardiorespiratory fitness may enhance knee stability and reduce the risk of lower limb injuries. Given the strong predictive value of VO₂max and LLMP for knee control, targeted training programs focusing on neuromuscular conditioning and aerobic capacity may be effective for injury prevention. Full article

Research on abdominal aortic aneurysms (AAAs) primarily focuses on developing a clear understanding of the initiation, progression, and treatment of AAA through improved model accuracy. High-fidelity hemodynamic and biomechanical predictions are essential for clinicians to optimize preoperative planning and minimize therapeutic risks. Computational fluid dynamics (CFDs), finite element analysis (FEA), and fluid-structure interaction (FSI) are widely used to simulate AAA hemodynamics and biomechanics. However, the accuracy of these simulations depends on the utilization of realistic and sophisticated boundary conditions (BCs), which are essential for properly integrating the AAA with the rest of the cardiovascular system. Recent advances in machine learning (ML) techniques have introduced faster, data-driven surrogates for AAA modeling. These approaches can accelerate segmentation, predict hemodynamics and biomechanics, and assess disease progression. However, their reliability depends on high-quality training data derived from CFDs and FEA simulations, where BC modeling plays a crucial role. Accurate BCs can enhance ML predictions, increasing the clinical applicability. This paper reviews existing BC models, discussing their limitations and technical challenges. Additionally, recent advancements in ML and data-driven techniques are explored, discussing their current states, future directions, common algorithms, and limitations. Full article

Background: Accurate estimation of myocardial material parameters is crucial to understand cardiac biomechanics and plays a key role in advancing computational modeling and clinical applications. Traditional inverse finite element (FE) methods rely on iterative optimization to infer these parameters, which is computationally expensive and time-consuming, limiting their clinical applicability. Methods: This study proposes a deep learning-based approach to rapidly and accurately estimate the left ventricular myocardial material parameters directly from routine cardiac magnetic resonance imaging (CMRI) data. A ResNet18-based model was trained on FEM-derived parameters from a dataset of 1288 healthy subjects. Results: The proposed model demonstrated high predictive accuracy on healthy subjects, achieving mean absolute errors of 0.0146 for $C_a$ and 0.0139 for $C_b$, with mean relative errors below 5.00%. Additionally, we evaluated the model on a small pathological subset (including ARV and HCM cases). The results revealed that while the model maintained strong performance on healthy data, the prediction errors in the pathological samples were higher, indicating increased challenges in modeling diseased myocardial tissue. Conclusion: This study establishes a computationally efficient and accurate deep learning framework for estimating myocardial material parameters, eliminating the need for time-consuming iterative FE optimization. While the model shows promising performance on healthy subjects, further validation and refinement are required to address its limitations in pathological conditions, thereby paving the way for personalized cardiac modeling and improved clinical decision-making. Full article

Background/Objectives: Postmortem changes in tissue stiffness and organ morphology are critical for forensic medicine and pathology. Shear wave elastography (SWE) has emerged as a non-invasive tool to assess tissue stiffness, yet its potential for postmortem interval estimation remains underexplored. While previous studies have demonstrated early postmortem alterations in tissue elasticity, the temporal progression of these changes in different organs is not fully understood. This study aims to investigate the temporal changes in liver and spleen stiffness during the postmortem period using SWE and to evaluate the predictive potential of elastographic parameters for postmortem interval estimation. Methods: Twelve male Sprague–Dawley rats were sacrificed via cervical dislocation following deep anesthesia. Postmortem liver and spleen measurements, including longitudinal and short diameters and SWE values (kPa), were recorded at 0, 2, 4, 6, 9, 12, 18, 24, and 36 h. All elastographic measurements were obtained using a 5 mm circular region of interest (ROI) for the liver and a 3 mm ROI for the spleen. Changes over time were analyzed using repeated measures ANOVA, with post hoc Bonferroni corrections applied where necessary. Additionally, Receiver Operating Characteristic (ROC) curve analysis and binary logistic regression analysis were performed to assess the predictive accuracy of SWE parameters in estimating postmortem time. Results: Postmortem liver and spleen stiffness exhibited a significant declining trend over time (p < 0.001, η² = 0.749 and η² = 0.810, respectively). Liver and spleen dimensions initially increased, reaching peak values around 6 h, followed by a gradual reduction. ROC analysis demonstrated that spleen SWE (AUC = 0.917) and liver SWE (AUC = 0.845) were the strongest predictors of early postmortem time. Binary logistic regression further confirmed that liver and spleen SWE were statistically significant predictors of postmortem time (p = 0.006 and p = 0.020, respectively). Conclusions: This study provides evidence that postmortem liver and spleen stiffness decline progressively over time, while organ dimensions exhibit a biphasic pattern. Elastographic parameters, particularly SWE values, demonstrated strong predictive accuracy in estimating early postmortem intervals. These findings suggest that SWE may serve as a valuable imaging modality for forensic applications, providing objective insights into postmortem biomechanical changes and time-of-death estimation. Further research should explore the applicability of SWE in different tissue types and under varying environmental conditions. Full article

Background/Objectives: The peri-implant soft tissue seal is crucial for the long-term success of subcrestally placed implants (SPIs). However, conventional biologic width—now referred to as supracrestal tissue attachment (STA)—models, originally developed for natural teeth, fail to account for the three-dimensional nature of peri-implant soft tissue adaptation. This study introduces a novel framework integrating the concepts of the transitional zone (TZ) and subcrestal zone (SZ) to systematically optimize peri-implant soft tissue architecture. Methods: A mathematical model was developed to determine the optimal implant placement depth by incorporating the emergence angle (EA), soft tissue thickness (STT), and peripheral crestal offset (PCO). Additionally, a three-dimensional peri-implant soft tissue analysis (3DSTA) approach utilizing cone beam computed tomography (CBCT) imaging was implemented to evaluate peri-implant soft tissue adaptation and emergence profile design. Clinical parameters were analyzed to establish guidelines for optimizing SPI placement depth and peri-implant soft tissue stability. Results: This study introduces the concept of self-sustained soft tissue (SSST), a biologically functional structure composed of the TZ and SZ, which enhances peri-implant health and stability. The proposed framework provides clinical guidelines for optimizing SPI placement depth, emergence profile contouring, and peri-implant soft tissue thickness to mitigate the risk of peri-implant mucositis. By shifting from a traditional two-dimensional perspective to a multidimensional analysis, this approach offers an evidence-based foundation for achieving biologically stable and esthetically predictable outcomes. Conclusions: The proposed three-dimensional model advances the understanding of peri-implant soft tissue adaptation by integrating novel anatomical and biomechanical concepts. By redefining peri-implant biologic width through the introduction of TZ and SZ, this study provides a structured framework for optimizing SPI placement and soft tissue management. Future research should focus on validating this model through histological studies and long-term clinical trials to refine its application in clinical practice. Full article

This study evaluates the biomechanical efficacy of clear aligners in closing anterior maxillary diastemas using enhanced force systems. While clear aligners offer esthetic and functional benefits, their predictability in controlling bodily movement and torque remains limited. This research investigates the effects of structural modifications, such as the addition of flowable resin to interdental embrasures and intrusive force application, on the force and moment characteristics during mesial bodily movement of maxillary central incisors. Experiments were conducted using 3D-printed maxillary models with a 6-axis force/torque sensor under controlled conditions. Four experimental groups were tested: Group 1 (0.3 mm mesial bodily shift), Group 2 (0.3 mm mesial shift + 0.1 mm intrusion), Group 3 (0.3 mm mesial shift with resin reinforcement), and Group 4 (0.3 mm mesial shift + 0.1 mm intrusion with resin reinforcement). The results showed that Groups 1 and 3 exhibited extrusive forces, while Groups 2 and 4 exhibited intrusive movement with minimized extrusion. Resin reinforcement significantly increased mesiodistal force application and reduced unwanted tipping and rotational moments, improving bodily movement efficiency. The addition of intrusive movement minimized extrusive forces but introduced a minor lingual inclination. The combination of both modifications provided the most controlled and efficient tooth movement. These results suggest that modifying clear aligners with localized structural enhancements can improve treatment predictability and efficiency. Clinically, the application of flowable resin enhancements offers a simple and effective approach to optimizing clear aligner therapy. Full article

Background: Elastography is an ultrasound-based imaging technology that allows for quantitative measurement of tissue stiffness and elasticity. In reproductive medicine, it is a potential non-invasive method for assessing ovarian activity, uterine contractility, and endometrial receptivity. While conventional ultrasound provides anatomical and vascular information, it does not assess biomechanical properties, which are important for understanding polycystic ovary syndrome (PCOS), predicting intrauterine insemination (IUI) success, and determining endometrial receptivity in in vitro fertilization (IVF). Methods: A systematic review was conducted in accordance with the PRISMA principles, and the protocol was recorded in PROSPERO. A comprehensive literature search was conducted across several databases to uncover studies that used real-time elastography (RTE) or shear wave elastography (SWE) for PCOS diagnosis, IUI result prediction, or endometrial receptivity evaluation in IVF. The risk of bias was assessed using the ROBINS-I technique. Results: Four studies fulfilled the inclusion criteria. One study indicated that PCOS patients had considerably increased ovarian stiffness, which supports elastography as a diagnostic marker. Another study found that increased uterine flexibility and decreased contractility were related with better IUI outcomes. A retrospective cohort research discovered that non-uniform endometrial echogenicity had no influence on IVF results. Furthermore, SWE successfully evaluated endometrial receptivity in unexplained infertility, with higher stiffness being related to reduced implantation potential. Conclusions: Elastography gives real-time, quantitative insights into reproductive biomechanics, with potential applications in infertility diagnosis and ART improvement. However, the absence of defined imaging procedures and confirmed clinical criteria prevent its broad use. More large-scale prospective investigations are required to improve elastographic parameters and define diagnostic cutoffs for clinical use. Full article

The primary aim of this scoping review was to identify practical risk factors associated with an elevated risk in anterior cruciate ligament injury (ACLI) in elite male field team athletes that can be applied meaningfully in screening tools by team support personnel. Five relevant databases were searched (SportsDISCUS, Medical Literature Analysis and Retrieval System Online, PsycINFO, Web of Science and Cumulative Index to Nursing and Allied Health Literature) following the PRISMA-ScR protocol using the criteria: (1) written in English and peer-reviewed; (2) full-text available; (3) discussed ACLI screening tests; (4) an elite athlete cohort; (5) males; (6) field team sport. The search identified 962 manuscripts, with nine manuscripts meeting the inclusion criteria. Field sports represented were soccer (n = 7), American football (n = 1), and a mixed-sport cohort of soccer, rugby, and field hockey (n = 1). Manuscripts reported modifiable risk factors (the joint range of motion n = 1, biomechanics n = 3, and strength n = 1) and non-modifiable (anatomical n = 2 and genetics n = 2). Whilst the joint range of motion screening indicated statistical significance to ACLI risk, there was little predictive value. Non-modifiable risk factors were significantly correlated to ACLI and reported a higher predictive capacity for ACLI risk. There is limited systematic research investigating and providing predictive insight for screening tests of ACLI risk in elite male team sport athletes. Future prospective investigations should consider the validity of ACLI screening tests in elite male field-based sport populations, and establish efficacy, so that sporting clubs can confidently implement screening tests of value into practice. Full article

Background/Objectives: This study aimed to examine how uncertainties in inertial properties and minimal sets of inertial parameters (MSIP) affect inverse-dynamics simulations of high-acceleration sport movements and to demonstrate that applying MSIP identified through the free vibration measurement method improves simulation accuracy. Methods: Monte Carlo simulations were performed for running, side-cutting, vertical jumping, arm swings, and leg swings by introducing uncertainties in inertial properties and MSIP. Results: These uncertainties significantly affect the joint torques and ground reaction forces and moments (GRFs&Ms), especially during large angular acceleration. The mass and longitudinal position of the center of gravity had strong effects. Subsequently, MSIP identified by our methods with free vibration measurement were applied to the same tasks, improving the accuracy of the predicted ground reaction forces compared with the standard regression-based estimates. The root mean square error decreased by up to 148 N. Conclusions: These results highlight that uncertainties in inertial properties and MSIP affected the calculated joint torques and GRFs&Ms, and combining experimentally identified MSIP with dynamics simulations enhances precision. These findings demonstrate that utilizing the MSIP from free vibration measurement in inverse dynamics simulations improves the accuracy of dynamic models in sports biomechanics, thereby providing a robust framework for precise biomechanical analyses. Full article