A Machine Learning Approach for Predicting Pedaling Force Profile in Cycling.

Accurate measurement of pedaling kinetics and kinematics is vital for optimizing rehabilitation, exercise training, and understanding musculoskeletal biomechanics. Pedal reaction force, the main external force in cycling, is essential for musculoskeletal modeling and closely correlates with lower-limb muscle activity and joint reaction forces. However, sensor instrumentation like 3-axis pedal force sensors is costly and requires extensive postprocessing. Recent advancements in machine learning (ML), particularly neural network (NN) models, provide promising solutions for kinetic analyses. In this study, an NN model was developed to predict radial and mediolateral forces, providing a low-cost solution to study pedaling biomechanics with stationary cycling ergometers. Fifteen healthy individuals performed a 2 min pedaling task at two different self-selected (58 ± 5 RPM) and higher (72 ± 7 RPM) cadences. Pedal forces were recorded using a 3-axis force system. The dataset included pedal force, crank angle, cadence, power, and participants' weight and height. The NN model achieved an inter-subject normalized root mean square error (nRMSE) of 0.15 ± 0.02 and 0.26 ± 0.05 for radial and mediolateral forces at high cadence, respectively, and 0.20 ± 0.04 and 0.22 ± 0.04 at self-selected cadence. The NN model's low computational time suits real-time pedal force predictions, matching the accuracy of previous ML algorithms for estimating ground reaction forces in gait.

Classification of the quality of canine and feline ventrodorsal and dorsoventral thoracic radiographs through machine learning.

Thoracic radiographs are an essential diagnostic tool in companion animal medicine and are frequently used as a part of routine workups in patients presenting for coughing, respiratory distress, cardiovascular diseases, and for staging of neoplasia. Quality control is a critical aspect of radiology practice in preventing misdiagnosis and ensuring consistent, accurate, and reliable diagnostic imaging. Implementing an effective quality control procedure in radiology can impact patient outcomes, facilitate clinical decision-making, and decrease healthcare costs. In this study, a machine learning-based quality classification model is suggested for canine and feline thoracic radiographs captured in both ventrodorsal and dorsoventral positions. The problem of quality classification was divided into collimation, positioning, and exposure, and then an automatic classification method was proposed for each based on deep learning and machine learning. We utilized a dataset of 899 radiographs of dogs and cats. Evaluations using fivefold cross-validation resulted in an F1 score and AUC score of 91.33 (95% CI: 88.37-94.29) and 91.10 (95% CI: 88.16-94.03), respectively. Results indicated that the proposed automatic quality classification has the potential to be implemented in radiology clinics to improve radiograph quality and reduce nondiagnostic images.

The Emergence of AI-Based Wearable Sensors for Digital Health Technology: A Review.

Disease diagnosis and monitoring using conventional healthcare services is typically expensive and has limited accuracy. Wearable health technology based on flexible electronics has gained tremendous attention in recent years for monitoring patient health owing to attractive features, such as lower medical costs, quick access to patient health data, ability to operate and transmit data in harsh environments, storage at room temperature, non-invasive implementation, mass scaling, etc. This technology provides an opportunity for disease pre-diagnosis and immediate therapy. Wearable sensors have opened a new area of personalized health monitoring by accurately measuring physical states and biochemical signals. Despite the progress to date in the development of wearable sensors, there are still several limitations in the accuracy of the data collected, precise disease diagnosis, and early treatment. This necessitates advances in applied materials and structures and using artificial intelligence (AI)-enabled wearable sensors to extract target signals for accurate clinical decision-making and efficient medical care. In this paper, we review two significant aspects of smart wearable sensors. First, we offer an overview of the most recent progress in improving wearable sensor performance for physical, chemical, and biosensors, focusing on materials, structural configurations, and transduction mechanisms. Next, we review the use of AI technology in combination with wearable technology for big data processing, self-learning, power-efficiency, real-time data acquisition and processing, and personalized health for an intelligent sensing platform. Finally, we present the challenges and future opportunities associated with smart wearable sensors.

An Adaptive Pedaling Assistive Device for Asymmetric Torque Assistant in Cycling.

Dynamic loads have short and long-term effects in the rehabilitation of lower limb joints. However, an effective exercise program for lower limb rehabilitation has been debated for a long time. Cycling ergometers were instrumented and used as a tool to mechanically load the lower limbs and track the joint mechano-physiological response in rehabilitation programs. Current cycling ergometers apply symmetrical loading to the limbs, which may not reflect the actual load-bearing capacity of each limb, as in Parkinson's and Multiple Sclerosis diseases. Therefore, the present study aimed to develop a new cycling ergometer capable of applying asymmetric loads to the limbs and validate its function using human tests. The instrumented force sensor and crank position sensing system recorded the kinetics and kinematics of pedaling. This information was used to apply an asymmetric assistive torque only to the target leg using an electric motor. The performance of the proposed cycling ergometer was studied during a cycling task at three different intensities. It was shown that the proposed device reduced the pedaling force of the target leg by 19% to 40%, depending on the exercise intensity. This reduction in pedal force caused a significant reduction in the muscle activity of the target leg (p < 0.001), without affecting the muscle activity of the non-target leg. These results demonstrated that the proposed cycling ergometer device is capable of applying asymmetric loading to lower limbs, and thus has the potential to improve the outcome of exercise interventions in patients with asymmetric function in lower limbs.

The importance of intervertebral disc material model on the prediction of mechanical function of the cervical spine.

BACKGROUND: Linear elastic, hyperelastic, and multiphasic material constitutive models are frequently used for spinal intervertebral disc simulations. While the characteristics of each model are known, their effect on spine mechanical response requires a careful investigation. The use of advanced material models may not be applicable when material constants are not available, model convergence is unlikely, and computational time is a concern. On the other hand, poor estimations of tissue's mechanical response are likely if the spine model is oversimplified. In this study, discrepancies in load response introduced by material models will be investigated. METHODS: Three fiber-reinforced C2-C3 disc models were developed with linear elastic, hyperelastic, and biphasic behaviors. Three different loading modes were investigated: compression, flexion and extension in quasi-static and dynamic conditions. The deformed disc height, disc fluid pressure, range of motion, and stresses were compared. RESULTS: Results indicated that the intervertebral disc material model has a strong effect on load-sharing and disc height change when compression and flexion were applied. The predicted mechanical response of three models under extension had less discrepancy than its counterparts under flexion and compression. The fluid-solid interaction showed more relevance in dynamic than quasi-static loading conditions. The fiber-reinforced linear elastic and hyperelastic material models underestimated the load-sharing of the intervertebral disc annular collagen fibers. CONCLUSION: This study confirmed the central role of the disc fluid pressure in spinal load-sharing and highlighted loading conditions where linear elastic and hyperelastic models predicted energy distribution different than that of the biphasic model.

3D Markerless asymmetry analysis in the management of adolescent idiopathic scoliosis.

BACKGROUND: Three dimensional (3D) markerless asymmetry analysis was developed to assess and monitor the scoliotic curve. While the developed surface topography (ST) indices demonstrated a strong correlation with the Cobb angle and its change over time, it was reported that the method requires an expert for monitoring the procedure to prevent misclassification for some patients. Therefore, this study aimed at improving the user-independence level of the previously developed 3D markerless asymmetry analysis implementing a new asymmetry threshold without compromising its accuracy in identifying the progressive scoliotic curves. METHODS: A retrospective study was conducted on 128 patients with Adolescent Idiopathic Scoliosis (AIS), with baseline and follow-up radiograph and surface topography assessments. The suggested "cut point" which was used to separate the deformed surfaces of the torso from the undeformed regions, automatically generated deviation patches corresponding to scoliotic curves for all analyzed surface topography scans. RESULTS: By changing the "cut point" in the asymmetry analysis for monitoring scoliotic curves progression, the sensitivity for identifying curve progression was increased from 68 to 75%, while the specificity was decreased from 74 to 59%, compared with the original method with different "cut point". CONCLUSIONS: These results lead to a more conservative approach in monitoring of scoliotic curves in clinical applications; smaller number of radiographs would be saved, however the risk of having non-measured curves with progression would be decreased.

Chondrocyte deformation during the unloading phase of cyclic compression loading.

Cell volume and shape changes play a pivotal role in cellular mechanotransduction, governing cellular responses to external loading. Understanding the dynamics of cell behavior under loading conditions is essential to elucidate cell adaptation mechanisms in physiological and pathological contexts. In this study, we investigated the effects of dynamic cyclic compression loading on cell volume and shape changes, comparing them with static conditions. Using a custom-designed platform which allowed for simultaneous loading and imaging of cartilage tissue, tissues were subjected to 100 cycles of mechanical loading while measuring cell volume and shape alterations during the unloading phase at specific time points. The findings revealed a transient decrease in cell volume (13%) during the early cycles, followed by a gradual recovery to baseline levels after approximately 20 cycles, despite the cartilage tissue not being fully recovered at the unloading phase. This observed pattern indicates a temporal cell volume response that may be associated with cellular adaptation to the mechanical stimulus through mechanisms related to active cell volume regulation. Additionally, this study demonstrated that cell volume and shape responses during dynamic loading were significantly distinct from those observed under static conditions. Such findings suggest that cells in their natural tissue environment perceive and respond differently to dynamic compared to static mechanical cues, highlighting the significance of considering dynamic loading environments in studies related to cellular mechanics. Overall, this research contributes to the broader understanding of cellular behavior under mechanical stimuli, providing valuable insights into their ability to adapt to dynamic mechanical loading.

Machine learning based prediction of image quality in prostate MRI using rapid localizer images.

Purpose: Diagnostic performance of prostate MRI depends on high-quality imaging. Prostate MRI quality is inversely proportional to the amount of rectal gas and distention. Early detection of poor-quality MRI may enable intervention to remove gas or exam rescheduling, saving time. We developed a machine learning based quality prediction of yet-to-be acquired MRI images solely based on MRI rapid localizer sequence, which can be acquired in a few seconds. Approach: The dataset consists of 213 (147 for training and 64 for testing) prostate sagittal T2-weighted (T2W) MRI localizer images and rectal content, manually labeled by an expert radiologist. Each MRI localizer contains seven two-dimensional (2D) slices of the patient, accompanied by manual segmentations of rectum for each slice. Cascaded and end-to-end deep learning models were used to predict the quality of yet-to-be T2W, DWI, and apparent diffusion coefficient (ADC) MRI images. Predictions were compared to quality scores determined by the experts using area under the receiver operator characteristic curve and intra-class correlation coefficient. Results: In the test set of 64 patients, optimal versus suboptimal exams occurred in 95.3% (61/64) versus 4.7% (3/64) for T2W, 90.6% (58/64) versus 9.4% (6/64) for DWI, and 89.1% (57/64) versus 10.9% (7/64) for ADC. The best performing segmentation model was 2D U-Net with ResNet-34 encoder and ImageNet weights. The best performing classifier was the radiomics based classifier. Conclusions: A radiomics based classifier applied to localizer images achieves accurate diagnosis of subsequent image quality for T2W, DWI, and ADC prostate MRI sequences.

Integration of Swin UNETR and statistical shape modeling for a semi-automated segmentation of the knee and biomechanical modeling of articular cartilage.

Simulation studies, such as finite element (FE) modeling, provide insight into knee joint mechanics without patient involvement. Generic FE models mimic the biomechanical behavior of the tissue, but overlook variations in geometry, loading, and material properties of a population. Conversely, subject-specific models include these factors, resulting in enhanced predictive precision, but are laborious and time intensive. The present study aimed to enhance subject-specific knee joint FE modeling by incorporating a semi-automated segmentation algorithm using a 3D Swin UNETR for an initial segmentation of the femur and tibia, followed by a statistical shape model (SSM) adjustment to improve surface roughness and continuity. For comparison, a manual FE model was developed through manual segmentation (i.e., the de-facto standard approach). Both FE models were subjected to gait loading and the predicted mechanical response was compared. The semi-automated segmentation achieved a Dice similarity coefficient (DSC) of over 98% for both the femur and tibia. Hausdorff distance (mm) between the semi-automated and manual segmentation was 1.4 mm. The mechanical results (max principal stress and strain, fluid pressure, fibril strain, and contact area) showed no significant differences between the manual and semi-automated FE models, indicating the effectiveness of the proposed semi-automated segmentation in creating accurate knee joint FE models. We have made our semi-automated models publicly accessible to support and facilitate biomechanical modeling and medical image segmentation efforts ( https://data.mendeley.com/datasets/k5hdc9cz7w/1 ).

A new scoliosis brace padding method based on trunk asymmetry for scoliosis treatment.

BACKGROUND: Pressure pads are used with scoliosis braces to adjust the magnitude and location of corrective forces that mechanically support the torso to correct the spine deformity. In the conventional brace (C.B.) design approaches, the location and shape of pads are determined based on the visual assessment of the clinician. The accuracy of this approach could be improved because it is limited to the clinician's expertise. The present study aimed to develop a new brace (N.B.) padding method based on trunk asymmetry for adolescents with idiopathic scoliosis and compare the efficacy of the developed method with C.B. in improving the Cobb angle and body posture symmetricity. METHODS: The trunk surface geometry was scanned using a 3-dimensional scanner. The best plane of symmetry was determined, and the original trunk was reflected in the plane of symmetry, creating the reflected trunk. The difference between the reflected and original trunks was computed and color-coded using deviation contour maps. The boundary of deformed regions, with a minimum of 6-mm deviation contour maps, was identified as the trim lines for brace pads. Eight participants were recruited and divided into conventional and new padding groups. The variation of Cobb angle and torso asymmetry parameters, including the trunk rotation and back surface rotation, as well as the brace satisfaction and trunk appearance perception of the 2 groups, were compared after 3 months of treatment. RESULTS: Cobb angle improved equally in the N.B. and C.B. groups. However, back surface rotation improved in the N.B. group (+49.6%) and worsened in the C.B. group (-6.8%). The mean trunk rotation was improved by 30% in the N.B. and further exacerbated by -2.2% in the C.B. group. The brace satisfaction and trunk appearance perception scores were higher in the N.B. than in the C.B. group, however not statistically significant. CONCLUSIONS: The present study showed that the proposed brace padding system improved the trunk appearance without negatively affecting the Cobb angle correction.

A numerical model for fibril remodeling in articular cartilage.

BACKGROUND: Collagen fibrils of articular cartilage have a distinct organization in mature human knee joints. It seems that a mechanobiological process drives the remodeling of newborn collagen fibrils with maturation. Therefore, the goal of the present study was to develop a collagen fibril remodeling algorithm that describes the unique collagen fibril organization in a 3D knee model. METHOD: A fibril-reinforced, biphasic cartilage model was used with a cuboid and a 3D human knee joint geometries. An isotropic collagen fibril distribution was assigned to the cartilage at the start of the analysis. Each fibril was rotated towards the direction that resulted in a maximum stretch at each time increment of the loading cycle. RESULTS: The resulting pattern for the collagen fibrils was compared with split line patterns of porcine knee joint cartilage and also data published in the literature. Fibrils on the articular surface had a radial pattern towards the geometrical centroid of the tibial and femoral cartilage. In the tibiofemoral contact regions of superficial zone, fibrils were oriented circumferentially and randomly. In the porcine samples, the split-line patterns were similar to those obtained theoretically. Depth-wise organization of fibril network was characterized by fibrils perpendicular to the subchondral bone in the deeper layers, and fibrils parallel to the surface of cartilage in the superficial zone. CONCLUSIONS: The maximum stretch criterion, coupled with a biphasic constitutive model, successfully predicted the collagen fibril organization observed in the articular cartilage throughout the depth and on the articular surface.

Machine learning can appropriately classify the collimation of ventrodorsal and dorsoventral thoracic radiographic images of dogs and cats.

OBJECTIVES: To determine the feasibility of machine learning algorithms for the classification of appropriate collimation of the cranial and caudal borders in ventrodorsal and dorsoventral thoracic radiographs. SAMPLES: 900 ventrodorsal and dorsoventral canine and feline thoracic radiographs were retrospectively acquired from the Picture Archiving and Communication system (PACs) system of the Ontario Veterinary College. PROCEDURES: Radiographs acquired from April 2020 to May 2021 were labeled by 1 radiologist in Summer of 2022 as either appropriately or inappropriately collimated for the cranial and caudal borders. A machine learning model was trained to identify the appropriate inclusion of the entire lung field at both the cranial and caudal borders. Both individual models and a combined overall inclusion model were assessed based on the combined results of both the cranial and caudal border assessments. RESULTS: The combined overall inclusion model showed a precision of 91.21% (95% CI [91, 91.4]), accuracy of 83.17% (95% CI [83, 83.4]), and F1 score of 87% (95% CI [86.8, 87.2]) for classification when compared with the radiologist's quality assessment. The model took on average 6 ± 1 second to run. CLINICAL RELEVANCE: Deep learning-based methods can classify small animal thoracic radiographs as appropriately or inappropriately collimated. These methods could be deployed in a clinical setting to improve the diagnostic quality of thoracic radiographs in small animal practice.

Automatic classification of symmetry of hemithoraces in canine and feline radiographs.

Purpose: Thoracic radiographs are commonly used to evaluate patients with confirmed or suspected thoracic pathology. Proper patient positioning is more challenging in canine and feline radiography than in humans due to less patient cooperation and body shape variation. Improper patient positioning during radiograph acquisition has the potential to lead to a misdiagnosis. Asymmetrical hemithoraces are one of the indications of obliquity for which we propose an automatic classification method. Approach: We propose a hemithoraces segmentation method based on convolutional neural networks and active contours. We utilized the U-Net model to segment the ribs and spine and then utilized active contours to find left and right hemithoraces. We then extracted features from the left and right hemithoraces to train an ensemble classifier, which include support vector machine, gradient boosting, and multi-layer perceptron. Five-fold cross-validation was used, thorax segmentation was evaluated by intersection over union (IoU), and symmetry classification was evaluated using precision, recall, area under curve, and F1 score. Results: Classification of symmetry for 900 radiographs reported an F1 score of 82.8%. To test the robustness of the proposed thorax segmentation method to underexposure and overexposure, we synthetically corrupted properly exposed radiographs and evaluated results using IoU. The results showed that the model's IoU for underexposure and overexposure dropped by 2.1% and 1.2%, respectively. Conclusions: Our results indicate that the proposed thorax segmentation method is robust to poor exposure radiographs. The proposed thorax segmentation method can be applied to human radiography with minimal changes.

The influence of equine hoof conformation on the initiation and progression of laminitis.

BACKGROUND: The health and performance of horses are significantly affected by diseases associated with the hoof. Laminitis is a critical hoof disease that causes pain and, potentially, severe hoof and bone pathology. OBJECTIVE: To generate an equine hoof finite element (FE) model to investigate the impact of normal and toe-in hoof conformations on the degeneration (decrease in elastic modulus) of the laminar junction (LJ), as occurs in chronic laminitis. STUDY DESIGN: Computer software modelling. METHODS: A hoof FE model was generated to investigate the biomechanics of hoof laminitis. A 3D model, consisting of nine components, was constructed from computed tomography scans of an equine left forelimb hoof. The model was loaded with 100 cycles of trotting. Two different centres of pressure (COP) paths representing normal and toe-in conformations were assigned to the model. LJ injury was modelled by degenerating the tissue's elastic modulus in the presence of excessive maximum principal stresses. RESULTS: FE models successfully showed findings similar to clinical observations, confirming third phalanx (P3) dorsal rotation, a symmetric distal displacement of the P3 (2 mm at the lateral and medial sides) in the normal model, and an asymmetric distal displacement of the P3 (4 mm at the lateral and 1.5 mm at the medial side) in the toe-in model. The proximal distance between P3 and the ground after LJ degeneration in the current model was significantly different from experimental measurements from healthy hooves (P < 0.01). MAIN LIMITATIONS: The inability to account for variations in population geometry and approximation of boundary conditions and system relations were the limitations of the current study. CONCLUSIONS: The distribution of LJ tissue degeneration was symmetric at the quarters in the normal hoof and in comparison, there was a lateral concentration of degeneration in the toe-in model.

HISTORIAL: La salud y el desempeño atlético de los caballos son afectados por patologías asociadas al casco. La laminitis es una enfermedad critica del casco que causa dolor y, potencialmente, patología severa del casco y ósea. OBJETIVO: Generar un modelo finito del casco equino para investigar el impacto de la conformación normal y del dedo-hacia-adentro sobre la degeneración (reducción del módulo elástico) de la unión laminar (UL), como ocurre en la laminitis crónica. DISEÑO DEL ESTUDIO: Modelado por computadora. MÉTODOS: Un modelo de elemento finito (EF) de casco fue generado para investigar la biomecánica de la laminitis en el casco. Un modelo 3D, que consistía de nueve componentes, fue construido a partir de imágenes de tomografía computarizada de un casco equino izquierdo. El modelo fue cargado con 100 ciclos de trote. Dos vías con centros de presión (VCP) distintos representando la conformación normal y dedo-hacia-adentro fueron asignadas al modelo. La lesión de la UL fue modelada degenerando el modelo elástico del tejido en la presencia de estrés principales excesivos máximos. RESULTADOS: Los modelos EF mostraron exitosamente hallazgos similares a las observaciones clínicas, confirmando que la rotación dorsal de la tercera falange (F3), con un desplazamiento distal simétrico de F3 (2 mm por medial y lateral) en el modelo normal, y un desplazamiento distal asimétrico de F3 (4 mm por lateral y 1.5 mm por medial) en el modelo dedo-hacia-adentro. La distancia proximal entre F3 y el suelo después de la degeneración de la UL en el modelo actual fue significativamente diferente de las mediciones experimentales de casco saludables (P < 0.01). LIMITACIONES DEL ESTUDIO: La inhabilidad de tomar en cuenta las variaciones en la geometría de la población y la aproximación de condiciones marginales, y relaciones de sistemas fueron las limitantes de este estudio. CONCLUSIONES: La distribución de la degeneración del tejido de la UL fue simétrico en los cuartos en el casco normal, hubo una concentración lateral de la degeneración en el modelo dedo-hacia-adentro. PALABRAS CLAVE: laminitis, conformación del casco del caballo, centro de presión, método de elemento finito, modelo hiperelástico.

An Investigation Into Different Measurement Techniques to Assess Equine Proximal Hoof Circumference.

Equine hoof conformation is integral to equine performance and soundness. Consequently, it is a major area of interest within the field of equine health. Researchers have measured several hoof shape parameters to study the hoof conformation. Proximal hoof circumference (PHC) is a primary hoof shape parameter, and its assessment may help to recognize the early stages of the development of changes in hoof morphology or poor hoof shape. Previous studies have mainly used a measuring tape to measure PHC. However, some doubts still exist regarding the reliability, repeatability and accuracy of measuring tape in this context. The current study conducted a technical comparison between the measuring tape and two alternative methods of 3D scanning and photogrammetry to measure PHC. Five equine limbs were collected from five adult horses, and the PHC of the limbs was measured using these three methods. The 3D scanner method was considered to be the highest accuracy and the reference for method comparisons. Pairwise correlations between the 3D scanner and the other two methods were conducted using a linear mixed model. The measuring tape and photogrammetry tended to overestimate the mean PHC compared to the 3D scanner by 0.96 mm (P > .05) and 2.2 mm (P < .05), respectively. In addition, an excellent interrater and intrarater correlation coefficient index was reported for the reliability of the tape measurements. The variation of the tape measurements was ±2 mm, which justified the use of measuring tape for PHC measurements in various clinical and horse management applications.

Efficacy of Computer-Aided Design and Manufacturing Versus Computer-Aided Design and Finite Element Modeling Technologies in Brace Management of Idiopathic Scoliosis: A Narrative Review.

The efficiency and design quality of scoliosis braces produced by the conventional casting method depends highly on the orthotist's experience. Recently, advanced engineering techniques have been used with the aim of improving the quality of brace design and associated clinical outcomes. Numerically controlled machine tools have provided enormous opportunities for reducing the manufacturing time and saving material. However, the effectiveness of computer-aided brace manufacturing for scoliosis curve improvement is controversial. This narrative review is aimed at comparing the efficacy of braces made by the conventional method with those made by two computer-aided methods: computer-aided design and manufacturing (CAD-CAM), and computer-aided design and finite element modeling (CAD-FEM). The comparison was performed on scoliosis parameters in coronal, sagittal, and transverse planes. Scientific databases were searched, and 11 studies were selected for this review. Because of the diversity of study designs, it was not possible to decisively conclude which brace-manufacturing method is most effective. Similar effectiveness in curve correction was found in the coronal plane for braces made by using advanced manufacturing and conventional methods. In the sagittal plane, modern braces seem to be more effective than traditional braces, but there is an ongoing debate among clinicians, about which CAD-CAM and CAD-FEM brace provides a better treatment outcome. The relative effectiveness of modern and conventional methods in correcting deformities in the transverse plane is also a controversial subject. Overall, advanced engineering design and production methods can be proposed as time- and cost-efficient approaches for scoliosis management. However, there is insufficient evidence yet to conclude that CAD-CAM, and CAD-FEM methods provide significantly better clinical outcomes than those of conventional methods in the treatment of scoliosis curve. Moreover, for some factors, such as molding and the patient's posture during the data acquisition, in brace curve-correction plan, the orthotist's experience and scoliosis curve flexibility should be explored to confidently compare the outcomes of conventional, CAD-CAM, and CAD-FEM methods.

Linear elastic and hyperelastic studies of equine hoof mechanical response at different hydration levels.

Most simulation studies on equine hoof biomechanics employed linear elastic (LE) material models. However, the equine hoof wall's stress-strain relationship is nonlinear and varies with hydration level. Therefore, it is essential to investigate the accuracy of the LE model compared to more advanced material models, such as hyperelastic (HE) or viscoelastic models. The current research investigated performances of LE and three HE models (Mooney-Rivlin, Neo-Hookean, and Marlow) in describing equine hoof's mechanical behavior using finite element (FE) analysis. In the first attempt, a rectangular tissue specimen was simulated using the previously published experimental data. The Marlow HE model predicted the hoof wall stress-strain curve more accurately than the LE, Mooney-Rivlin, and Neo-Hookean models. The LE model accuracy, compared with the experimental results, varied within the reported range of the strain. However, the Marlow HE model perfectly matched the experimental data for a wide range of strains. In the second attempt, the entire hoof, including nine associated tissues, was modeled from computed tomography (CT) scans of an equine forelimb, and analyzed at trotting and standing modes of locomotion. The effect of environmental humidity on the hoof wall material properties was incorporated at four hydration levels; 0%, 53%, 75%, and 100%. The simulation results of the LE and HE models indicated that the minimum principal strain distribution on the hoof wall remained under 2% for various hydration levels and gait conditions. The numerical results of the Marlow HE model demonstrated better agreement with published experimental data compared to the LE, Mooney-Rivlin, and Neo-Hookean models. Higher hydration levels significantly increased the strains - a potential explanation could be the fact that the higher hydration levels decreased stiffness of the hoof wall tissues and ultimately increased strains. Higher ground reaction forces increased the von Mises stress at various points in the hoof wall, especially in the quarter regions and close to the coronet, where cracks and fractures are found more often in the physiological conditions.

The influence of equine limb conformation on the biomechanical responses of the hoof: An in vivo and finite element study.

Hoof conformation plays a key role in equine locomotion. Toe-in conformation is an abnormal condition characterized by inward deviation of the limb from its frontal axis. Several studies have documented differences in hoof deformation and hoof kinematics in horses with toe-in and normal hoof conformations. However, the reason behind this has yet to be understood. The present study hypothesizes that a different center of pressure (COP) path underneath the hoof is the cause of different deformation patterns and hoof kinematics in toe-in hooves. In vivo measurements and finite element (FE) analysis were conducted to test the hypothesis. A normal and a toe-in limb were considered for in vivo strain measurements. Strains were measured at three different sites on the hoof wall, and the stride characteristics were investigated using video recording. The magnitude of the minimum principal strain measured at the medial aspect of the toe-in hoof was much lower relative to the normal hoof. Furthermore, the toe-in hoof had a different movement pattern (plaiting) compared to the normal hoof. In the second study, an entire hoof model was simulated from computed tomography (CT) scans of an equine left forelimb. The Neo-Hookean hyperelastic material model was used, and the hoof was under dynamic loading over a complete stride at the trot. Two different COP paths associated with normal and toe-in conformations were assigned to the model. The FE model produced the same in vivo minimum principal strain distributions and successfully showed the different kinematics of the toe-in and normal hooves.

Chondrocyte Deformations Under Mild Dynamic Loading Conditions.

Dynamic deformation of chondrocytes are associated with cell mechanotransduction and thus may offer a new understanding of the mechanobiology of articular cartilage. Despite extensive research on chondrocyte deformations for static conditions, work for dynamic conditions remains rare. However, it is these dynamic conditions that articular cartilage in joints are exposed to everyday, and that seem to promote biological signaling in chondrocytes. Therefore, the objective of this study was to develop an experimental technique to determine the in situ deformations of chondrocytes when the cartilage is dynamically compressed. We hypothesized that dynamic deformations of chondrocytes vastly differ from those observed under steady-state static strain conditions. Real-time chondrocyte geometry was reconstructed at 10, 15, and 20% compression during ramp compressions with 20% ultimate strain, applied at a strain rate of 0.2% s-1, followed by stress relaxation. Dynamic compressive chondrocyte deformations were non-linear as a function of nominal strain, with large deformations in the early and small deformations in the late part of compression. Early compression (up to about 10%) was associated with chondrocyte volume loss, while late compression (> ~ 10%) was associated with cell deformation but minimal volume loss. Force continued to decrease for 5 min in the stress-relaxation phase, while chondrocyte shape/volume remained unaltered after the first minute of stress-relaxation.

Effect of collagen fibril distributions on the crack profile in articular cartilage.

BACKGROUND AND OBJECTIVE: Cartilage cracks and fissures may occur due to certain daily life activities such as sports practice, blunt trauma, and matrix fibrillation during early osteoarthritis. These cracks could further grow at the macroscopic level, alter the load distribution pattern in the matrix, limit the joint range of motion, and disturb chondrocytes synthesis. Cracks' shape and deformations in the loaded cartilage may affect the subsequent mechanobiological processes in the long term, likely because of the altered fluid exchange and excessive local deformations in the vicinity of the damage site. The fibrillar structure of the cartilage matrix appeared to have a protective effect against excessive deformations and tissue failure. Hence, in the present study, a fibril reinforced biphasic cartilage model was used to assess the potential role of different fibril orientations on the profile of a vertical crack in cartilage after applying a compressive load. METHODS: A 20 × 20 × 1.5 mm3 cartilage model was developed with a 0.7 mm length V-shape cut at the center. Using an impermeable indenter, a 27% compression was applied to immature, mature, and isotropic cartilage models. Each of immature and mature groups had 4 different split line directions with respect to the cut edges, including 90°, 45°, 0°, and random orientation. The latter represented the disrupted collagen fibril orientations in early osteoarthritis. The model was verified with the experimental results in the literature. RESULTS: In the superficial zones, the larger angle between the split lines and cut edges resulted in a wider cut opening. In the absence of collagen fibrils, the isotropic model resulted in a closed edge profile. Also, under a consistently applied compression, the OA model, with random collagen fibril distribution on its surface, had the smallest load-bearing capacity compared to the other models. CONCLUSIONS: Findings highlighted a primary role of collagen fibrils on the cut profile, which was more pronounced at dynamic rather than static conditions. Split lines perpendicular to the cut edges had some protective effects against the large dislocation of cut edges. These findings could be utilized to develop engineered tissues less susceptible to rupture. Moreover, the outcome of the present study can explain the potential causes of the crack propagation path reported in the literature.