Modeling individual-specific human optic nerve head biomechanics. Part I: IOP-induced deformations and influence of geometry

Glaucoma, the second most common cause of blindness worldwide, is an ocular disease characterized by progressive loss of retinal ganglion cell (RGC) axons. Biomechanical factors are thought to play a central role in RGC loss, but the specific mechanism underlying this disease remains unknown. Our goal was to characterize the biomechanical environment in the optic nerve head (ONH)—the region where RGC damage occurs—in human eyes. Post mortem human eyes were imaged, fixed at either 5 or 50 mmHg pressure and processed histologically to acquire serial sections through the ONH. Three-dimensional models of the ONH region were reconstructed from these sections and embedded in a generic scleral shell to create a model of an entire eye. We used finite element simulations to quantify the effects of an acute change in intraocular pressure from 5 to 50 mmHg on the ONH biomechanical environment. Computed strains varied substantially within the ONH, with the pre-laminar neural tissue and the lamina cribrosa showing the greatest strains. The mode of strain having the largest magnitude was third principal strain (compression), reaching 12–15% in both the lamina cribrosa and the pre-laminar neural tissue. Shear strains were also substantial. The distribution of strains in all ONH tissues was remarkably similar between eyes. Inter-individual variations in ONH geometry (anatomy) have only modest effects on ONH biomechanics, and may not explain inter-individual susceptibility to elevated intraocular pressure. Consistent with previous results using generic ONH models, the displacements of the vitreo-retinal interface and the anterior surface of the lamina cribrosa can differ substantially, suggesting that currently available optical imaging methods do not provide information of the acute deformations within ONH tissues. Predicted strains within ONH tissues are potentially biologically significant and support the hypothesis that biomechanical factors contribute to the initial insult that leads to RGC loss in glaucoma. Ian A. Sigal now a post-doctoral research fellow at Ocular Biomechanics Laboratory, Devers Eye Institute, Legacy Health Research. Portland, OR, USA. (isigal@deverseye.org).     

Compressive mechanical properties of rat and pig optic nerve head

Glaucoma is the leading cause of irreversible blindness worldwide. Elevated intraocular pressure (IOP), the primary risk factor for glaucoma, is thought to induce abnormally high strains in optic nerve head (ONH) tissues, which ultimately result in retinal ganglion cell damage and vision loss. The mechanisms by which excessive deformations result in vision loss remain incompletely understood. The ability of computational and in vitro models of the ONH to provide insight into these mechanisms, in many cases, depends on our ability to replicate the physiological environment, which in turn requires knowledge of tissue biomechanical properties. The majority of mechanical data published to date regarding the ONH has been obtained from tensile testing, yet compression has been shown to be the main mode of deformation in the ONH under elevated IOP. We have thus tested pig and rat ONH tissue using unconfined cyclic compression. The material constants C₁, obtained from fitting the stress vs. strain data with a neo-Hookean material model, were 428 [367, 488] Pa and 64 [53, 76] Pa (mean [95% Confidence Interval]) for pig and rat optic nerve head, respectively. Additionally, we investigated the effects of strain rate and tissue storage on C1 values. These data will inform future efforts to understand and replicate the in vivo biomechanical environment of the ONH.     

On the unimportance of constitutive models in computing brain deformation for image-guided surgery

Imaging modalities that can be used intra-operatively do not provide sufficient details to confidently locate the abnormalities and critical healthy areas that have been identified from high-resolution pre-operative scans. However, as we have shown in our previous work, high quality pre-operative images can be warped to the intra-operative position of the brain. This can be achieved by computing deformations within the brain using a biomechanical model. In this paper, using a previously developed patient-specific model of brain undergoing craniotomy-induced shift, we conduct a parametric analysis to investigate in detail the influences of constitutive models of the brain tissue. We conclude that the choice of the brain tissue constitutive model, when used with an appropriate finite deformation solution, does not affect the accuracy of computed displacements, and therefore a simple linear elastic model for the brain tissue is sufficient.     

A cellular solid model of the lamina cribrosa: mechanical dependence on morphology

The biomechanics of the optic nerve head (ONH) may underlie many of the potential mechanisms that initiate the characteristic vision loss associated with primary open angle glaucoma. Therefore, it is important to characterize the physiological levels of stress and strain in the ONH and how they may change in relation to material properties, geometry, and microstructure of the tissue. An idealized, analytical microstructural model of the ONH load bearing tissues was developed based on an octagonal cellular solid that matched the porosity and pore area of morphological data from the lamina cribrosa (LC). A complex variable method for plane stress was applied to relate the geometrically dependent macroscale loads in the sclera to the microstructure of the LC, and the effect of different geometric parameters, including scleral canal eccentricity and laminar and scleral thickness, was examined. The transmission of macroscale load in the LC to the laminar microstructure resulted in stress amplifications between 2.8 and 24.5xIOP. The most important determinants of the LC strain were those properties pertaining to the sclera and included Young's modulus, thickness, and scleral canal eccentricity. Much larger strains were developed perpendicular to the major axis of an elliptical canal than in a circular canal. Average strain levels as high as 5% were obtained for an increase in IOP from 15 to 50 mm Hg.     

On the importance of modelling organ geometry and boundary conditions for predicting three-dimensional prostate deformation

The use of an ultrasound probe or a needle guide during biopsy deforms both the rectal wall and the prostate, resulting in lesion motion. An accurate patient-specific finite element (FE)-based biomechanical model can be used to predict prostate deformations. In this study, an FE model of a prostate phantom is developed using magnetic resonance images, while soft-tissue elasticity is estimated in vivo using an ultrasound-based acoustic radiation force impulse imaging technique. This study confirms that three-dimensional FE-predicted prostate deformation is predominantly dependent on accurate modelling of prostate geometry and boundary conditions. Upon application of various compressive displacements, our results show that a linear elastic FE model can accurately predict prostate deformations. The maximum global error between FE-predicted simulations and experimental results is 0.76 mm. Moreover, the effect of including the urethra, puboprostatic ligament and urinary bladder on prostate deformations is investigated by a sensitivity study.     

Patient-specific model of brain deformation: application to medical image registration

This contribution presents finite element computation of the deformation field within the brain during craniotomy-induced brain shift. The results were used to illustrate the capabilities of non-linear (i.e. accounting for both geometric and material non-linearities) finite element analysis in non-rigid registration of pre- and intra-operative magnetic resonance images of the brain. We used patient-specific hexahedron-dominant finite element mesh, together with realistic material properties for the brain tissue and appropriate contact conditions at boundaries. The model was loaded by the enforced motion of nodes (i.e. through prescribed motion of a boundary) at the brain surface in the craniotomy area. We suggest using explicit time-integration scheme for discretised equations of motion, as the computational times are much shorter and accuracy, for practical purposes, the same as in the case of implicit integration schemes. Application of the computed deformation field to register (i.e. align) the pre-operative images with the intra-operative ones indicated that the model very accurately predicts the displacements of the tumour and the lateral ventricles even for limited information about the brain surface deformation. The prediction accuracy improves when information about deformation of not only exposed (during craniotomy) but also unexposed parts of the brain surface is used when prescribing loading. However, it appears that the accuracy achieved using information only about the deformation of the exposed surface, that can be determined without intra-operative imaging, is acceptable. The presented results show that non-linear biomechanical models can complement medical image processing techniques when conducting non-rigid registration. Important advantage of such models over the previously used linear ones is that they do not require unrealistic assumptions that brain deformations are infinitesimally small and brain stress-strain relationship is linear.     

Picosecond timescale rigid-helix and side-chain motions in deoxymyoglobin

The contribution of rigidbody motions to the atomic trajectories in a 100 ps molecular dynamics simulation of deoxymyoglobin is examined. Two typesof rigid-body motions are considered: one in which the helices are rigid units and one in which the side-chains are rigid units. Using a quaternionbased algorithm, fits of the rigid reference structures are made to each time frame of the simulation to derive trajectories of the rigid-body motions. The fitted trajectories are analysed in terms of atomic position fluctuations, mean-square displacements as a function of time, velocity autocorrelation functions and densities of states. The results are compared with the corresponding quantities calculated from the full trajectory. The relative contribution of the rigid helix motions to the helix atom dynamics depends on which quantity is examined and on which subset of atoms is chosen: rigid-helix motions contribute 86% of the rms helix backbone atomic position fluctuations, but 30% of the helix,: atom (backbone and side-chain) mean square displacements and only 1.1% of total kinetic energy. Only very low-frequency motions contribute to the rigid-helix dynamics; the rigid-body analysis allows characteristic rigid-helix vibrations to be identified and described. Treating the side-chains as rigid bodies is foundto be an excellent approximation to both their diffusive and vibrationalmean-square displacements: 96% of side-chain atom mean-square displacements originate from rigid side-Chain motions. However, the errors in theside-chain atomic positional fits are not always small. An analysis is madeof factors contributing to the positional error for different types of side-chain. © Wiley-Liss, Inc.     

Analysis of carotid artery deformation in different head and neck positions for maxillofacial catheter navigation in advanced oral cancer treatment

ABSTRACT: BACKGROUND: To improve the accuracy of catheter navigation, it is important to develop a method to predict shifts of carotid artery (CA) bifurcations caused by intraoperative deformation. An important factor affecting the accuracy of electromagnetic maxillofacial catheter navigation systems is CA deformations. We aimed to assess CA deformation in different head and neck positions. METHODS: Using two sets of computed tomography angiography (CTA) images of six patients, displacements of the skull (maxillofacial segments), C1--C4 cervical vertebrae, mandible (mandibular segment), and CA along with its branches were analyzed. Segmented rigid bones around CA were considered the main causes of CA deformation. After superimposition of maxillofacial segments, C1--C4 and mandible segments were superimposed separately for displacement measurements. Five bifurcation points (vA--vE) were assessed after extracting the CA centerline. A new standardized coordinate system, regardless of patient-specific scanning positions, was employed. It was created using the principal axes of inertia of the maxillofacial bone segments of patients. Position and orientation parameters were transferred to this coordinate system. CA deformation in different head and neck positions was assessed. RESULTS: Absolute shifts in the center of gravity in the bone models for different segments were C1, 1.02 +/- 0.9; C2, 2.18 +/- 1.81; C3, 4.25 +/- 3.85; C4, 5.90 +/- 5.14; and mandible, 1.75 +/- 2.76 mm. Shifts of CA bifurcations were vA, 5.52 +/- 4.12; vB, 4.02 +/- 3.27; vC, 4.39 +/- 2.42; vD, 4.48 +/- 1.88; and vE, 2.47 +/- 1.32. Displacements, position changes, and orientation changes of C1--C4 segments as well as the displacements of all CA bifurcation points were similar in individual patients. CONCLUSIONS: CA deformation was objectively proven as an important factor contributing to errors in maxillofacial navigation. Our study results suggest that small movements of the bones around CA can result in small CA deformations. Although patients' faces were not fixed properly during CT scanning, C1--C4 and vA--vE displacements were similar in individual patients. We proposed a novel method for accumulation of the displacement data, and this study indicated the importance of surrounding bone displacements in predicting CA bifurcation.     

Investigation of the XCAT phantom as a validation tool in cardiac MRI tracking algorithms

PurposeTo describe our magnetic resonance imaging (MRI) simulated implementation of the 4D digital extended cardio torso (XCAT) phantom to validate our previously developed cardiac tracking techniques. Real-time tracking will play an important role in the non-invasive treatment of atrial fibrillation with MRI-guided radiosurgery. In addition, to show how quantifiable measures of tracking accuracy and patient-specific physiology could influence MRI tracking algorithm design.MethodsTwenty virtual patients were subjected to simulated MRI scans that closely model the proposed real-world scenario to allow verification of the tracking technique’s algorithm. The generated phantoms provide ground-truth motions which were compared to the target motions output from our tracking algorithm. The patient-specific tracking error, e_p, was the 3D difference (vector length) between the ground-truth and algorithm trajectories. The tracking errors of two combinations of new tracking algorithm functions that were anticipated to improve tracking accuracy were studied. Additionally, the correlation of key physiological parameters with tracking accuracy was investigated.ResultsOur original cardiac tracking algorithm resulted in a mean tracking error of 3.7 ± 0.6 mm over all virtual patients. The two combinations of tracking functions demonstrated comparable mean tracking errors however indicating that the optimal tracking algorithm may be patient-specific.ConclusionsCurrent and future MRI tracking strategies are likely to benefit from this virtual validation method since no time-resolved 4D ground-truth signal can currently be derived from purely image-based studies.     

Biomechanical wall properties of human intracranial aneurysms resected following surgical clipping (IRRAs Project)

Background and purposeIndividual rupture risk assessment of intracranial aneurysms is a major issue in the clinical management of asymptomatic aneurysms. Aneurysm rupture occurs when wall tension exceeds the strength limit of the wall tissue. At present, aneurysmal wall mechanics are poorly understood and thus, risk assessment involving mechanical properties is inexistent. Aneurysm computational hemodynamics studies make the assumption of rigid walls, an arguable simplification. We therefore aim to assess mechanical properties of ruptured and unruptured intracranial aneurysms in order to provide the foundation for future patient-specific aneurysmal risk assessment. This work also challenges some of the currently held hypotheses in computational flow hemodynamics research.MethodsA specific conservation protocol was applied to aneurysmal tissues following clipping and resection in order to preserve their mechanical properties. Sixteen intracranial aneurysms (11 female, 5 male) underwent mechanical uniaxial stress tests under physiological conditions, temperature, and saline isotonic solution. These represented 11 unruptured and 5 ruptured aneurysms. Stress/strain curves were then obtained for each sample, and a fitting algorithm was applied following a 3-parameter (C₁₀, C₀₁, C₁₁) Mooney–Rivlin hyperelastic model. Each aneurysm was classified according to its biomechanical properties and (un)rupture status.ResultsTissue testing demonstrated three main tissue classes: Soft, Rigid, and Intermediate. All unruptured aneurysms presented a more Rigid tissue than ruptured or pre-ruptured aneurysms within each gender subgroup. Wall thickness was not correlated to aneurysmal status (ruptured/unruptured). An Intermediate subgroup of unruptured aneurysms with softer tissue characteristic was identified and correlated with multiple documented risk factors of rupture.ConclusionThere is a significant modification in biomechanical properties between ruptured aneurysm, presenting a soft tissue and unruptured aneurysms, presenting a rigid material. This finding strongly supports the idea that a biomechanical risk factor based assessment should be utilized in the to improve the therapeutic decision making.     

The collagen fibril architecture in the lamina cribrosa and peripapillary sclera predicted by a computational remodeling approach

The biomechanics of the optic nerve head is assumed to play an important role in ganglion cell loss in glaucoma. Organized collagen fibrils form complex networks that introduce strong anisotropic and nonlinear attributes into the constitutive response of the peripapillary sclera (PPS) and lamina cribrosa (LC) dominating the biomechanics of the optic nerve head. The recently presented computational remodeling approach (Grytz and Meschke in Biomech Model Mechanobiol 9:225–235, 2010) was used to predict the micro-architecture in the LC and PPS, and to investigate its impact on intraocular pressure–related deformations. The mechanical properties of the LC and PPS were derived from a microstructure-oriented constitutive model that included the stretch-dependent stiffening and the statistically distributed orientations of the collagen fibrils. Biomechanically induced adaptation of the local micro-architecture was captured by allowing collagen fibrils to be reoriented in response to the intraocular pressure–related loading conditions. In agreement with experimental observations, the remodeling algorithm predicted the existence of an annulus of fibrils around the scleral canal in the PPS, and a predominant radial orientation of fibrils in the periphery of the LC. The peripapillary annulus significantly reduced the intraocular pressure–related expansion of the scleral canal and shielded the LC from high tensile stresses. The radial oriented fibrils in the LC periphery reinforced the LC against transversal shear stresses and reduced LC bending deformations. The numerical approach presents a novel and reasonable biomechanical explanation of the spatial orientation of fibrillar collagen in the optic nerve head.     

Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time; Application to non-rigid neuroimage registration

Long computation times of non-linear (i.e. accounting for geometric and material non-linearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery. This contribution presents real-time patient-specific computation of the deformation field within the brain for six cases of brain shift induced by craniotomy (i.e. surgical opening of the skull) using specialised non-linear finite element procedures implemented on a graphics processing unit (GPU). In contrast to commercial finite element codes that rely on an updated Lagrangian formulation and implicit integration in time domain for steady state solutions, our procedures utilise the total Lagrangian formulation with explicit time stepping and dynamic relaxation. We used patient-specific finite element meshes consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the preoperative and intraoperative images indicated that the models very accurately predict the intraoperative deformations within the brain. For each case, computing the brain deformation field took less than 4 s using an NVIDIA Tesla C870 GPU, which is two orders of magnitude reduction in computation time in comparison to our previous study in which the brain deformation was predicted using a commercial finite element solver executed on a personal computer.     

Estimating joint kinematics from skin motion observation: modelling and validation

Modelling of soft tissue motion is required in many areas, such as computer animation, surgical simulation, 3D motion analysis and gait analysis. In this paper, we will focus on the use of modelling of skin deformation during 3D motion analysis. The most frequently used method in 3D human motion analysis involves placing markers on the skin of the analysed segment which is composed of the rigid bone and the surrounding soft tissues. Skin and soft tissue deformations introduce a significant artefact which strongly influences the resulting bone position, orientation and joint kinematics. For this study, we used a statistical solid dynamics approach which is a combination of several previously reported tools: the point cluster technique (PCT) and a Kalman filter which was added to the PCT. The methods were tested and evaluated on controlled human-arm motions, using an optical motion capture system (Vicon(TM)). The addition of a Kalman filter to the PCT for rigid body motion estimation results in a smoother signal that better represents the joint motion. Calculations indicate less signal distortion than when using a digital low-pass filter. Furthermore, adding a Kalman filter to the PCT substantially reduces the dispersion of the maximal and minimal instantaneous frequencies. For controlled human movements, the result indicated that adding a Kalman filter to the PCT produced a more accurate signal. However, it could not be concluded that the proposed Kalman filter is better than a low-pass filter for estimation of the motion. We suggest that implementation of a Kalman filter with a better biomechanical motion model will be more likely to improve the results.     

A biomechanical model of mammographic compressions

A number of biomechanical models have been proposed to improve nonrigid registration techniques for multimodal breast image alignment. A deformable breast model may also be useful for overcoming difficulties in interpreting 2D X-ray projections (mammograms) of 3D volumes (breast tissues). If a deformable model could accurately predict the shape changes that breasts undergo during mammography, then the model could serve to localize suspicious masses (visible in mammograms) in the unloaded state, or in any other deformed state required for further investigations (such as biopsy or other medical imaging modalities). In this paper, we present a validation study that was conducted in order to develop a biomechanical model based on the well-established theory of continuum mechanics (finite elasticity theory with contact mechanics) and demonstrate its use for this application. Experimental studies using gel phantoms were conducted to test the accuracy in predicting mammographic-like deformations. The material properties of the gel phantom were estimated using a nonlinear optimization process, which minimized the errors between the experimental and the model-predicted surface data by adjusting the parameter associated with the neo-Hookean constitutive relation. Two compressions (the equivalent of cranio-caudal and medio-lateral mammograms) were performed on the phantom, and the corresponding deformations were recorded using a MRI scanner. Finite element simulations were performed to mimic the experiments using the estimated material properties with appropriate boundary conditions. The simulation results matched the experimental recordings of the deformed phantom, with a sub-millimeter root-mean-square error for each compression state. Having now validated our finite element model of breast compression, the next stage is to apply the model to clinical images.     

Analysis of mechanical parameters on the thromboembolism using a patient-specific computational model

Ischemic stroke is a major cause of death and long-term disabilities worldwide. In this paper, we aim to represent a comprehensive simulation of the motion of emboli through cerebrovascular network within patient-specific computational model. The model consists of major arteries of the circle of Willis reconstructed from magnetic resonance angiography images, pulsatile flow and emboli with different sizes and material properties. Here, the fluid–structure interactions method was used to simulate the motion of deformable and rigid emboli through cerebral arteries. Hemodynamic changes in the circle of Willis due to the entrance of embolus are observed. The effect of material properties on the distribution ratio and dynamics of motion of the emboli in the cerebral arterial network is also analyzed. Our results reveal that as the rigidity of emboli increases, higher proportion of them tend to enter to the larger arteries (e.g., middle cerebral artery). Scrutinizing the amount of stress acting on the emboli represented in this paper can broaden our understanding of the rheological phenomenon (e.g., lysis or growth of emboli during embolism). The approach of considering different material properties of the thrombus in a patient-specific computational model not only enable us to better understand the roll of biomechanical parameters causing the embolism, but also lead to a better clinical decision making to manage patients with stroke.     

Estimating joint kinematics from skin motion observation: modelling and validation

Modelling of soft tissue motion is required in many areas, such as computer animation, surgical simulation, 3D motion analysis and gait analysis. In this paper, we will focus on the use of modelling of skin deformation during 3D motion analysis. The most frequently used method in 3D human motion analysis involves placing markers on the skin of the analysed segment which is composed of the rigid bone and the surrounding soft tissues. Skin and soft tissue deformations introduce a significant artefact which strongly influences the resulting bone position, orientation and joint kinematics. For this study, we used a statistical solid dynamics approach which is a combination of several previously reported tools: the point cluster technique (PCT) and a Kalman filter which was added to the PCT. The methods were tested and evaluated on controlled human-arm motions, using an optical motion capture system (Vicon^TM).

The addition of a Kalman filter to the PCT for rigid body motion estimation results in a smoother signal that better represents the joint motion. Calculations indicate less signal distortion than when using a digital low-pass filter. Furthermore, adding a Kalman filter to the PCT substantially reduces the dispersion of the maximal and minimal instantaneous frequencies. For controlled human movements, the result indicated that adding a Kalman filter to the PCT produced a more accurate signal. However, it could not be concluded that the proposed Kalman filter is better than a low-pass filter for estimation of the motion. We suggest that implementation of a Kalman filter with a better biomechanical motion model will be more likely to improve the results.     

An experimental and analytic study of the dynamic properties of the human leg

Certain problems in the dynamics of the human body are characterized by large displacements of the parts of the body compared to the deformations of the tissues themselves. In such problems, it is convenient to think of the human body as a chain of rigid links, representing the anatomical segments, with joints between the rigid links representing the articulations of the human body.

Skeletal muscles are capable of creating torques at the joints of the body. The joint torques of the rigid link model should portray the static strength of skeletal muscle, the degradation of muscle strength with rate of shortening, the feedback control of the stretch reflex, and the viscoelastic properties of the muscles, tendons, and joint capsules.

In this study a sinusoidal test is performed upon the knee joints of nine subjects. The increment of knee moment required to flex and extend the knee slightly for various conditions of knee angle, knee angular velocity, and steady knee moment is measured. The hip angle is maintained constant. After the effects of leg inertia are removed, the resulting data are shown to obey a Maxwell fluid model in which the model coefficients depend upon the absolute value of the knee moment.     

Multiscale modeling of macromolecular conformational changes combining concepts from rigidity and elastic network theory

The development of a two-step approach for multiscale modeling of macromolecular conformational changes is based on recent developments in rigidity and elastic network theory. In the first step, static properties of the macromolecule are determined by decomposing the molecule into rigid clusters by using the graph-theoretical approach FIRST and an all-atom representation of the protein. In this way, rigid clusters are not limited to consist of residues adjacent in sequence or secondary structure elements as in previous studies. Furthermore, flexible links between rigid clusters are identified and can be modeled as such subsequently. In the second step, dynamical properties of the molecule are revealed by the rotations-translations of blocks approach (RTB) using an elastic network model representation of the coarse-grained protein. In this step, only rigid body motions are allowed for rigid clusters, whereas links between them are treated as fully flexible. The approach was tested on a data set of 10 proteins that showed conformational changes on ligand binding. For efficiency, coarse-graining the protein results in a remarkable reduction of memory requirements and computational times by factors of 9 and 27 on average and up to 25 and 125, respectively. For accuracy, directions and magnitudes of motions predicted by our approach agree well with experimentally determined ones, despite embracing in extreme cases >50% of the protein into one rigid cluster. In fact, the results of our method are in general comparable with when no or a uniform coarse-graining is applied; and the results are superior if the movement is dominated by loop or fragment motions. This finding indicates that explicitly distinguishing between flexible and rigid regions is advantageous when using a simplified protein representation in the second step. Finally, motions of atoms in rigid clusters are also well predicted by our approach, which points to the need to consider mobile protein regions in addition to flexible ones when modeling correlated motions.     

Experimental platform to facilitate novel back brace development for the improvement of spine stability

Abstract

The spine or ‘back’ has many functions including supporting our body frame whilst facilitating movement, protecting the spinal cord and nerves and acting as a shock absorber. In certain instances, individuals may develop conditions that not only cause back pain but also may require additional support for the spine. Common movements such as twisting, standing and bending motions could exacerbate these conditions and intensify this pain. Back braces can be used in certain instances to constrain such motion as part of an individual’s therapy and have existed as both medical and retail products for a number of decades. Arguably, back brace designs have lacked the innovation expected in this time. Existing designs are often found to be heavy, overly rigid, indiscrete and largely uncomfortable. In order to facilitate the development of new designs of back braces capable of being optimised to constrain particular motions for specific therapies, a numerical and experimental design strategy has been devised, tested and proven for the first time. The strategy makes use of an experimental test rig in conjunction with finite element analysis simulations to investigate and quantify the effects of back braces on flexion, extension, lateral bending and torsional motions as experienced by the human trunk. This paper describes this strategy and demonstrates its effectiveness through the proposal and comparison of two novel back brace designs.