Mechanical analysis of deep tissue injury during sitting in patients with spinal cord injury via parametric finite element model

Smart Cushions with Machine Learning-Enhanced Force Sensors for Pressure Injury Risk Assessment

Prolonged sitting can easily result in pressure injury (PI) for certain people who have had strokes or spinal cord injuries. There are not many methods available for tracking contact surface pressure and shear force to evaluate the PI risk. Here, we propose a smart cushion that uses two-dimensional force sensors (2D-FSs) to measure the pressure and shear force in the buttocks. A machine learning algorithm is then used to compute the shear stresses in the gluteal muscles, which helps to determine the PI risk. The 2D-FS consists of a ferroelectret coaxial sensor (FCS) unit placed atop a ferroelectret film sensor (FFS) unit, allowing it to detect both vertical and horizontal forces simultaneously. To characterize and calibrate, two experimental approaches are applied: one involves simultaneously applying two perpendicular forces, and one involves applying a single force. To separate the two forces, the 2D-FS is decoupled using a deep neural network technique. Multiple FCSs are embedded to form a smart cushion, and a genetic algorithm-optimized backpropagation neural network is proposed and trained to predict the shear strain in the buttocks to prevent PI. By tracking the danger of PI, the smart cushion based on 2D-FSs may be further connected with home-based intelligent care platforms to increase patient equality for spinal cord injury patients and lower the expense of nursing or rehabilitation care.

Identification of constitutive materials of bi-layer soft tissues from multimodal indentations

The personalisation of finite element models is an important problem in the biomechanical fields where subject-specific analyses are fundamental, particularly in studying soft tissue mechanics. The personalisation includes the choice of the constitutive law of the model's material, as well as the choice of the material parameters. In vivo identification of the material properties of soft tissues is challenging considering the complex behaviour of soft tissues that are, among other things, non-linear hyperelastic and heterogeneous. Hybrid experimental-numerical methods combining in vivo indentations and inverse finite element analyses are common to identify these material parameters. Yet, the uniqueness and the uncertainty of the multi-material hyperelastic model have not been evaluated. This study presents a sensitivity analysis performed on synthetic indentation data to investigate the identification uncertainties of the material parameters in a bi-material thigh phantom. Synthetic numerical data, used to replace experimental measurements, considered several measurement modalities: indenter force and displacement, stereo-camera 3D digital image correlation of the indented surface, and ultrasound B-mode images. A finite element model of the indentation was designed with either Ogden-Moerman or Mooney-Rivlin constitutive laws for both materials. The parameters' identifiability (i.e. the possibility of converging to a unique parameter set within an acceptable margin of error) was assessed with various cost functions formulated using the different synthetic data sets. The results underline the need for multiple experimental modalities to reduce the uncertainty of the identified parameters. Additionally, the experimental error can impede the identification of a unique parameter set, and the cost function depends on the constitutive law. This study highlights the need for sensitivity analyses before the design of the experimental protocol. Such studies can also be used to define the acceptable range of errors in the experimental measurement. Eventually, the impact of the evaluated uncertainty of the identified parameters should be further investigated according to the purpose of the finite element modelling.

Proximal femoral bionic nail-a novel internal fixation system for the treatment of femoral neck fractures: a finite element analysis

Introduction: Currently, cannulated screws (CSs) and dynamic hip screws (DHSs) are widely used for the treatment of femoral neck fractures, but the postoperative complications associated with these internal fixations remain high. In response to this challenge, our team proposes a new approach involving triangular-supported fixation and the development of the proximal femoral bionic nail (PFBN). The primary objective of this study is to investigate the biomechanical differences among CSs, DHSs, and the PFBN in their capacity to stabilize femoral neck fractures. Methods: A normal proximal femur model was constructed according to the CT data of a normal healthy adult. A femoral neck fracture model was constructed and fixed with CSs, DHSs, and the PFBN to simulate the fracture fixation model. Abaqus 6.14 software was used to compare the biomechanical characters of the three fracture fixation models. Results: The maximum stresses and displacements of the normal proximal femur were 45.35 MPa and 2.83 mm, respectively. Under axial loading, the PFBN was more effective than DHSs and CSs in improving the stress concentration of the internal fixation and reducing the peak values of von Mises stress, maximum principal stress, and minimum principal stress. The PFBN fixation model exhibits superior overall and fracture section stability in comparison to both the DHS fixation model and the CS fixation model under axial loading. Notably, the maximum stress and peak displacement of the PFBN and bone were lower than those of the DHS and CS fixation models under bending and torsional loading. Conclusion: The PFBN shows considerable improvement in reducing stress concentration, propagating stress, and enhancing the overall stability in the femoral neck fracture fixation model compared to DHSs and CSs. These enhancements more closely correspond to the tissue structure and biomechanical characteristics of the proximal femur, demonstrating that the PFBN has great potential for therapeutic purposes in treating femoral neck fractures.

Computational assessment on the impact of collagen fiber orientation in cartilages on healthy and arthritic knee kinetics/kinematics

BACKGROUND

The inhomogeneous distribution of collagen fiber in cartilage can substantially influence the knee kinematics. This becomes vital for understanding the mechanical response of soft tissues, and cartilage deterioration including osteoarthritis (OA). Though the conventional computational models consider geometrical heterogeneity along with fiber reinforcements in the cartilage model as material heterogeneity, the influence of fiber orientation on knee kinetics and kinematics is not fully explored. This work examines how the collagen fiber orientation in the cartilage affects the healthy (intact knee) and arthritic knee response over multiple gait activities like running and walking.

METHODS

A 3D finite element knee joint model is used to compute the articular cartilage response during the gait cycle. A fiber-reinforced porous hyper elastic (FRPHE) material is used to model the soft tissue. A split-line pattern is used to implement the fiber orientation in femoral and tibial cartilage. Four distinct intact cartilage models and three OA models are simulated to assess the impact of the orientation of collagen fibers in a depth wise direction. The cartilage models with fibers oriented in parallel, perpendicular, and inclined to the articular surface are investigated for multiple knee kinematics and kinetics.

FINDINGS

The comparison of models with fiber orientation parallel to articulating surface for walking and running gait has the highest elastic stress and fluid pressure compared with inclined and perpendicular fiber-oriented models. Also, the maximum contact pressure is observed to be higher in the case of intact models during the walking cycle than for OA models. In contrast, the maximum contact pressure is higher during running in OA models than in intact models. Additionally, parallel-oriented models produce higher maximum stresses and fluid pressure for walking and running gait than proximal-distal-oriented models. Interestingly, during the walking cycle, the maximum contact pressure with intact models is approximately three times higher than on OA models. In contrast, the OA models exhibit higher contact pressure during the running cycle.

INTERPRETATION

Overall, the study indicates that collagen orientation is crucial for tissue responsiveness. This investigation provides insights into the development of tailored implants.

The relationship between shear wave velocity in transverse carpal ligament and carpal tunnel pressure: A finite element analysis

Elevated carpal tunnel pressure in carpal tunnel syndrome (CTS) patients is one of the major causes of nerve damage but cannot be measured non-invasively. This study proposed to use shear wave velocity (SWV) in the transverse carpal ligament (TCL) to measure the surrounding carpal tunnel pressure. The relationship between the carpal tunnel pressure and the SWV in the TCL was investigated through a subject-specific carpal tunnel finite element model reconstrued by MRI imaging. Parametric analysis was conducted to study the effect of TCL Young's modulus and carpal tunnel pressure on the TCL SWV. The SWV in TCL was found to be strongly dependent on the carpal tunnel pressure and TCL Young's modulus. The calculated SWV ranged from 8.0 m/s to 22.6 m/s under a combination of carpal tunnel pressure (0-200 mmHg) and TCL Young's modulus (1.1-11 MPa). An empirical equation was used to fit the relationship between the SWV in TCL and carpal tunnel pressure, with TCL Young's modulus as a confounding factor. The equation proposed in this study provided an approach to estimate carpal tunnel pressure by measuring the SWV in the TCL for a potential non-invasive diagnosis of CTS and may shed light on the mechanical nerve damage mechanism.

The effect of thickness and elastic modulus of the anterior talofibular ligament on anterior ankle joint stiffness: A subject-specific finite element study

Ankle sprain is a frequent type of sports injury leading to lateral ligament injury. The anterior talofibular ligament (ATFL) is a primary ligamentous stabilizer of the ankle joint and typically the most vulnerable ligament injured in a lateral ankle sprain (LAS). This study aimed to quantitively investigate the effect of the thickness and elastic modulus of ATFL on anterior ankle joint stiffness (AAJS) by developing nine subject-specific finite element (FE) models under acute injury, chronic injury, and control conditions of ATFL. A 120 N forward force was applied at the posterior calcaneus leading to an anterior translation of the calcaneus and talus to simulate the anterior drawer test (ADT). In the results, the ratio of the forward force to the talar displacement was used to assess the AAJS, which increased by 5.85% in the acute group and decreased by 19.78% in the chronic group, compared to those of the control group. An empirical equation described the relationship between AAJS, thickness, and elastic modulus (R-square 0.98). The equation proposed in this study provided an approach to quantify AAJS and revealed the effect of the thickness and the elastic modulus of ATFL on ankle stability, which may shed light on the potential diagnosis of lateral ligament injury.

Stiffening of the gluteal muscle increased the intramuscular stress: An in-silico implication of deep tissue injury

Objectives

Deep tissue injury is a common form of pressure ulcers in muscle tissues under bony prominences caused by sustained pressure or shear, which has a great impact on patients with restricted mobility such as spinal cord injury. Frequent spasms in spinal cord injury patients featured by muscle stiffening may be one of the factors leading to deep tissue injury. The purpose of this study was to investigate the relationship between the gluteal muscle shear modulus and intramuscular compressive/shear stress/strain.

Methods

A semi-3D finite element model of the human buttock was established using COMSOL software and the acquired biomechanical data were analyzed through Pearson correlation and Spearman correlation.

Results

Results showed that the compressive stress, strain energy density, and average von Mises stress increased with the increase of the gluteal muscle shear modulus.

Conclusion

These results may indicate muscle stiffening caused by muscle spasms could lead to higher deep tissue injury development risk as well as shed light on effective treatments for relieving muscular sclerosis mechanically.