Search Results (242)

(1) Background: The exploration of various machine learning (ML) algorithms for classifying the state of Lumbar Intervertebral Discs (IVD) in orthopedic patients is the focus of this study. The classification is based on six key biomechanical features of the pelvis and lumbar spine. Although previous research has demonstrated the effectiveness of ML models in diagnosing IVD pathology using imaging modalities, there is a scarcity of studies using biomechanical features. (2) Methods: The study utilizes a dataset that encompasses two classification tasks. The first task classifies patients into Normal and Abnormal based on their IVDs (2C). The second task further classifies patients into three groups: Normal, Disc Hernia, and Spondylolisthesis (3C). The performance of various ML models, including decision trees, support vector machines, and neural networks, is evaluated using metrics such as accuracy, AUC, recall, precision, F1, Kappa, and MCC. These models are trained on two open-source datasets, using the PyCaret library in Python. (3) Results: The findings suggest that an ensemble of Random Forest and Logistic Regression models performs best for the 2C classification, while the Extra Trees classifier performs best for the 3C classification. The models demonstrate an accuracy of up to 90.83% and a precision of up to 91.86%, highlighting the effectiveness of ML models in diagnosing IVD pathology. The analysis of the weight of different biomechanical features in the decision-making processes of the models provides insights into the biomechanical changes involved in the pathogenesis of Lumbar IVD abnormalities. (4) Conclusions: This research contributes to the ongoing efforts to leverage data-driven ML models in improving patient outcomes in orthopedic care. The effectiveness of the models for both diagnosis and furthering understanding of Lumbar IVD herniations and spondylolisthesis is outlined. The limitations of AI use in clinical settings are discussed, and areas for future improvement to create more accurate and informative models are suggested. Full article

Background/Objectives: Long-term work-related musculoskeletal disorders are predominantly influenced by factors such as the duration, intensity, and repetitive nature of load lifting. Although traditional ergonomic assessment tools can be effective, they are often challenging and complex to apply due to the absence of a streamlined, standardized framework. Recently, integrating wearable sensors with artificial intelligence has emerged as a promising approach to effectively monitor and mitigate biomechanical risks. This study aimed to evaluate the potential of machine learning models, trained on postural sway metrics derived from an inertial measurement unit (IMU) placed at the lumbar region, to classify risk levels associated with load lifting based on the Revised NIOSH Lifting Equation. Methods: To compute postural sway parameters, the IMU captured acceleration data in both anteroposterior and mediolateral directions, aligning closely with the body’s center of mass. Eight participants undertook two scenarios, each involving twenty consecutive lifting tasks. Eight machine learning classifiers were tested utilizing two validation strategies, with the Gradient Boost Tree algorithm achieving the highest accuracy and an Area under the ROC Curve of 91.2% and 94.5%, respectively. Additionally, feature importance analysis was conducted to identify the most influential sway parameters and directions. Results: The results indicate that the combination of sway metrics and the Gradient Boost model offers a feasible approach for predicting biomechanical risks in load lifting. Conclusions: Further studies with a broader participant pool and varied lifting conditions could enhance the applicability of this method in occupational ergonomics. Full article

Grassland degradation and reduced yields are often linked to the root soil composite of perennial alfalfa roots. This study introduces a novel modeling approach to accurately characterize root biomechanical properties, assist in the design of soil-loosening and root-cutting tools. Our model conceptualizes the root as a composite structure of cortex and stele, applying transversely isotropic properties to the stele and isotropic properties to the cortex. Material parameters were derived from longitudinal tension, longitudinal compression, transverse compression, and shear tests. The constitutive model of stele was Hashin failure criteria, accounting for differences in tensile and compressive strengths. Results reveal that root tensile strength mainly depends on the stele, with its tensile properties exceeding compressive and transverse strengths by 4–10 times. In non-longitudinal tensile stress scenarios, like shear and transverse compression tests, the new model demonstrated superior accuracy over conventional models. Results of shear tests were further validated using non-parametric statistical analysis. This study provides a finite element method (FEM) modeling approach that, by integrating root anatomical features and biomechanical properties, significantly enhances simulation accuracy. This provides a tool for designing low-energy consumption components in grassland degradation restoration and conservation tillage. Full article

Study Design: This was a single-institution, retrospective cohort study. Objective: The objective of this study was to assess a surgical technique for spinal reconstruction after corpectomy, integrating an allograft/autograft within a vertebral body replacement cage linked to spinal rods via pedicle screws. This method aims to enhance biomechanical stability and promote long-term fusion without cage endcaps. Summary of Background data: Recent advancements in spinal surgery feature innovative constructs that improve healing and fusion rates. FDA-approved mesh cages provide enhanced stability and superior fusion with fewer complications. Our approach combines allografts/autografts with vertebral replacements, using a pedicle screw through the cage for significant biomechanical enhancement. Methods: Two patients undergoing cervical and lumbar spinal reconstructions due to different pathologies were selected. The surgical technique involved shaping the allograft/autograft to fit precisely within the cage, extending beyond its ends to facilitate fusion at both ends, and securing the construct to the spinal rods with pedicle screws for added stability. Patient outcomes were assessed based on post-operative stability, fusion rates, and the presence of any complications. Results: Both cases successfully utilized the technique, achieving stabilization and fusion. Improvements were noted in post-operative recovery. There were no instances of cage subsidence, or any significant complications directly related to the novel construct. Conclusions: Our case series highlights a post-corpectomy reconstruction technique involving a mesh cage construct integrated with an autograft/allograft and connected to posterior instrumentation for enhanced stability. This technique was applied successfully in two cases, demonstrating its feasibility, durability, and potential to promote biological integration. Further studies with larger cohorts and extended follow-up periods are necessary to refine the approach for wider clinical use. Full article

The ovine cervical spine model has been established as a representative model of the human cervical spine in the current literature, and is the most commonly used large animal model in studies investigating pathogenesis and treatment strategies for intervertebral disc (IVD) degeneration. However, existing data regarding morphometry, biomechanical profiles and the microscopic features of a physiological ovine cervical IVD remain scarce. Hence, the aim of this study was to perform a multimodal morphometric, biomechanical and histologic evaluation of a normal ovine cervical IVD. For this purpose, nine ovine cervical IVDs were harvested from three female sheep, and subjected to morphometrical, biomechanical and histologic analyses. The biomechanical assessment included the performance of cyclic compression, creepand compressive strength tests in a controlledlaboratory environment. Histological evaluation was performed using hematoxylin–eosin, Masson’s trichrome and Alcian blue staining. The results from the morphometric analysis showed that the range of disc heights was 4–9 mm in all surfaces, featuring a constant increase from cranial to caudal levels. Biomechanical evaluation revealed that cyclic loading for 20 cycles was necessary for preconditioning so that the repeatability of the force–displacement hysteresis response is present. The critical failure point was defined at 15.5 MPa, whereas Young’s modulus of elasticity was 1.2 MPa. The histologic assessment demonstrated the presence of a concentric arrangement of collagen lamellae in external annulus fibrosus, along with the sparsely organized internal nucleus pulposus. Ovine cervical IVD represents a complex structure with distinct features that should be considered by researchers in this field in order to optimize the reliability and validity of testing results. Full article

The quadriceps angle, knowns as the Q-angle, is an anatomical feature of the human body that is still largely unknown and unstudied despite its initial discovery in the 1950s. The strength disparities between male and female athletes are largely determined by the Q-angle. In spite of a growing number of women participating in sports such as track, tennis, soccer, gymnastics, basketball, volleyball, swimming, and softball, studies investigating injuries in this group are scanty. Even though the Q-angle has been the subject of many studies carried out all over the world, a review of the literature regarding its effects on health and injury risk in female athletes has not yet been completed. The aim of this review is to examine the crucial role of the Q-angle in the biomechanics of the knee joint and its effect on performance and injury risk, particularly in female athletes. Furthermore, we highlight the greater likelihood of knee-related injuries seen in female athletes being caused by the Q-angle. Athletes, coaches, healthcare professionals, and athletic trainers can better comprehend and prepare for the benefits and drawbacks resulting from the Q-angle by familiarizing themselves with the research presented in this review. Full article

Adult-Acquired Flatfoot Deformity (AAFD) is a progressive orthopedic condition causing the collapse of the foot’s medial longitudinal arch, often linked with injuries to the plantar arch’s passive stabilizers, such as the spring ligament (SL) and plantar fascia. Conventional treatment typically involves replacing the SL with synthetic material grafts, which, while providing mechanical support, lack the biological compatibility of native ligaments. In response to this shortcoming, our study developed an electrospun, twisted polymeric graft made of polycaprolactone (PCL) and type B gelatin (GT), enhanced with graphene oxide (GO), a two-dimensional nanomaterial, to bolster biomechanical attributes. The addition of GO aimed to match the native ligamentous tissue’s mechanical strength, with the PCL-GT-GO 2.0% blend demonstrating an optimal Young’s modulus of 240.75 MPa. Furthermore, the graft showcased excellent biocompatibility, evidenced by non-hemolytic reactions, suitable wettability and favorable platelet aggregation—essential features for promoting cell adhesion and proliferation. An MTT assay revealed cell viability exceeding 80% after 48 h of exposure, highlighting the potential of the graft as a regenerative scaffold for affected ligaments. Computational modeling of the human foot across various AAFD stages assessed the graft’s in situ performance, with the PCL-GT-OG 2.0% graft efficiently preventing plantar arch collapse and offering hindfoot pronator support. Our study, based on in silico simulations, suggests that this bioengineered graft holds significant promise as an alternative treatment in AAFD surgery, marking a leap forward in the integration of advanced materials science for enhanced patient care. Full article

This study investigates the innovative design of a bicycle saddle by incorporating sustainable ergonomics, universal design principles, and systematic innovation methods. Initially, the literature related to bicycle saddle design and its impact on the human body during riding was analyzed. The TRIZ contradiction matrix was then used to identify relevant invention principles, which served as references for the innovative design of the bicycle saddle. Biomechanics and the human–machine system analysis within human factors engineering were applied to ensure the innovative design is ergonomic and user-friendly. The design features a horizontally expandable and foldable bicycle saddle, enhancing its adaptability and sustainability. Universal design principles were applied to make the innovative design more accessible to the general public, and the prototype was simulated using Inventor drawing software. The research results include: (1) An innovative bicycle saddle design with horizontal expansion and folding functions is proposed. This design divides the saddle into three components, enabling the left and right parts to expand or retract based on user preferences. (2) A bicycle backrest design featuring vertical adjustability is introduced. It incorporates a quick-release adjustment mechanism at the junction of the backrest and saddle, allowing users to freely adjust the backrest height. (3) A quick-operation bicycle saddle design is presented, utilizing quick-release screws to facilitate the swift operation of the horizontal expansion and folding mechanisms. This validation method confirmed that the innovative design meets both sustainable ergonomic standards and user expectations. The systematic innovation approach used in this study can serve as a valuable reference for future research and design applications. Full article

Background: Alzheimer’s disease (AD), the most prevalent form of dementia, is a leading neurodegenerative disorder currently affecting approximately 55 million individuals globally, a number projected to escalate to 139 million by 2050. Despite extensive research spanning several decades, the cure for AD remains at a developing stage. The only existing therapeutic options are limited to symptom management, and are often accompanied by adverse side effects. The pathological features of AD, including the accumulation of beta-amyloid plaques and tau protein tangles, result in progressive neuronal death, synaptic loss, and brain atrophy, leading to significant cognitive decline and a marked reduction in quality of life. Objective: In light of the shortcomings of existing pharmacological interventions, this review explores the potential of photobiomodulation (PBM) as a non-invasive therapeutic option for AD. PBM employs infrared light to facilitate cellular repair and regeneration, focusing on addressing the disease’s underlying biomechanical mechanisms. Method: This paper presents a comprehensive introduction to the mechanisms of PBM and an analysis of preclinical studies evaluating its impact on cellular health, cognitive function, and disease progression in AD.The review provides a comprehensive overview of the various wavelengths and application methods, evaluating their efficacy in mitigating AD-related symptoms. Conclusions: The findings underscore the significant potential of PBM as a safe and effective alternative treatment for Alzheimer’s disease, emphasizing the necessity for further research and clinical trials to establish its therapeutic efficacy conclusively. Full article

Research shows that treadmill shock-absorbing devices can reduce the impact of ground reaction forces on the knee and ankle joints during running. Most existing treadmills use fixed or passive shock absorption, meaning their shock-absorbing systems do not actively adjust to changes in ground reaction forces (GRFs). Methods: This study establishes a mathematical model integrating human motion biomechanics and treadmill running surfaces, analyzing the relationships between various parameters affecting the system. Ultimately, an optimal shock-absorbing treadmill control system is designed, utilizing a microcontroller as the main control unit, airbags for shock absorption, and a widely used foot pressure testing system. Objective: The goal is to more effectively prevent running injuries caused by excessive foot pressure. Compared to conventional shock absorption systems, this design features an active multilevel adjustment function with higher precision in regulation. Results: The experimental results demonstrate that the ground reaction force (GRF) generated by the optimal shock-absorbing treadmill control system is reduced by up to 10% compared to that of a conventional shock-absorbing treadmill. Conclusions: This leads to a smaller impact force on the knees due to foot pressure, resulting in better injury prevention outcomes. Full article

Changes in biomechanical properties such as elasticity modulus, viscosity, and poroelastic features are linked to the health status of biological tissues. Ultrasound elastography is a non-invasive imaging tool that quantitatively maps these biomechanical characteristics for diagnostic and treatment monitoring purposes. Mathematical models are essential in ultrasound elastography as they convert the raw data obtained from tissue displacement caused by ultrasound waves into the images observed by clinicians. This article reviews the available mathematical frameworks of continuum mechanics for extracting the biomechanical characteristics of biological tissues in ultrasound elastography. Continuum-mechanics-based approaches such as classical viscoelasticity, elasticity, and poroelasticity models, as well as nonlocal continuum-based models, are described. The accuracy of ultrasound elastography can be increased with the recent advancements in continuum modelling techniques including hyperelasticity, biphasic theory, nonlocal viscoelasticity, inversion-based elasticity, and incorporating scale effects. However, the time taken to convert the data into clinical images increases with more complex models, and this is a major challenge for expanding the clinical utility of ultrasound elastography. As we strive to provide the most accurate imaging for patients, further research is needed to refine mathematical models for incorporation into the clinical workflow. Full article

The mechanisms responsible for the growth and development of vascular beds in intestinal villi during postnatal ontogenesis remain enigmatic. For instance, according to the current consensus, in the sprouting type of angiogenesis, there is no blood flow in the rising capillary sprout. However, it is known that biomechanical forces resulting from blood flow play a key role in these processes. Here, we present evidence for the existence of the intussusception type of angiogenesis during the postnatal development of micro-vessel patterns in the intestinal villi of rats. This process is based on the high-level flattening of blood capillaries on the flat surfaces of intestinal villi, contacts among the opposite apical plasma membrane of endothelial cells in the area of inter-endothelial contacts, or the formation of bridges composed of blood leucocytes or local microthrombi. We identified factors that, in our opinion, ensure the splitting of the capillary lumen and the formation of two parallel vessels. These phenomena are in agreement with previously described features of intussusception angiogenesis. Full article

Optimizing the regeneration process of surgically created anastomoses (blood vessels, intestines, nerves) is an important topic in surgical research. One of the most interesting parameter groups is related to the biomechanical properties of the anastomoses. Depending on the regeneration process and its influencing factors, tensile strength and other biomechanical features may change during the healing process. Related to the optimal specimen size, the range and accuracy of measurements, and applicability, we have developed a custom-tailored microcontroller-based device. In this paper, we describe the hardware and software configuration of the latest version of the device, including experiences and comparative measurements of tensile strength and elasticity of artificial materials and biopreparate tissue samples. The machine we developed was made up of easily obtainable parts and can be easily reproduced on a low budget. The basic device can apply a force of up to 40 newtons, and can grasp a 0.05–1 cm wide, 0.05–1 cm thick tissue. The length of the test piece on the rail should be between 0.3 and 5 cm. Low production cost, ease of use, and detailed data recording make it a useful tool for experimental surgical research. Full article

Body balancing is a complex task that includes the coordination of muscles, tendons, bones, ears, eyes, and the brain. Imbalance or disequilibrium is the inability to maintain the center of gravity. Perpetuating body balance plays an important role in preventing us from falling or swaying. Biomechanical tests and video analysis can be performed to analyze body imbalance. The musculoskeletal system is one of the fundamental systems by which our balance or equilibrium is sustained and our upright posture is maintained. Electromyogram (EMG) and ground reaction force (GRF) monitoring can be utilized in cases where a rapid response to body imbalance is a necessity. Body balance also depends on visual stimuli that can be either real or virtual. Researchers have used virtual reality (VR) to predict motion sickness and analyze heart rate variability, as well as in rehabilitation. VR can also be used to induce body imbalance in a controlled way. In this research, body imbalance was induced in a controlled way by playing an Oculus game and, simultaneously, EMG and GRF were recorded. Features were extracted from the EMG and were then fed to a machine learning algorithm. Several machine learning algorithms were tested and upon 10-fold cross-validation; a minimum accuracy of 71% and maximum accuracy of 98% were achieved by Gaussian Naïve Bayes and Gradient Boosting classifiers, respectively, in the classification of imbalance and its intensities. This research can be incorporated into various rehabilitative and therapeutic systems. Full article

Background: The utilization of hemodynamic parameters, whose estimation is often cumbersome, can fasten diagnostics and decision-making related to congenital heart diseases. The main goal of this study is to investigate the relationship between hemodynamic and morphometric features of the thoracic aorta and to construct corresponding predictive models. Methods: Multi-slice spiral computed tomography images of the aortas of patients with coarctation diagnoses and patients without cardiac or vascular diseases were evaluated to obtain numerical models of the aorta and branches of the aortic arch. Hemodynamic characteristics were estimated in key subdomains of the aorta and three branches using computational fluid dynamics methods. The key morphometric features (diameters) were calculated at locations in proximity to the domains, where hemodynamic characteristics are evaluated. Results: The functional dependencies for velocities and pressure on the corresponding diameters have been fitted, and a metamodel has been constructed employing the predicted values from these models. Conclusions: The metamodel demonstrated high accuracy in classifying aortas into their respective types, thereby confirming the adequacy of the predicted hemodynamic characteristics by morphometric characteristics. The proposed methodology is applicable to other heart diseases without fundamental changes. Full article