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This study exploits a novel musculoskeletal finite element (MS-FE) spine model to evaluate the post-fusion (L4-L5) alterations in adjacent segment kinetics.Unlike the existing MS models with idealized representation of spinal joints, this model predicts stress/strain distributions in all passive tissues while organically coupled to a MS model. This generic (in terms of musculature and material properties) model uses population-based in vivo vertebral sagittal rotations, gravity loads, and an optimization algorithm to calculate muscle forces. Simulations represent individuals with an intact L4-L5, a preoperative severely degenerated L4-L5 (by reducing the disc height by ~ 60% and removing the nucleus incompressibility), and a postoperative fused L4-L5 segment with either a fixed or an altered lumbopelvic rhythm with respect to the intact condition (based on clinical observations). Changes in spine kinematics and back muscle cross-sectional areas (due to intraoperative injuries) are considered based on in vivo data while simulating three activities in upright/flexed postures.Postoperative changes in some adjacent segment kinetics were found considerable (i.e., larger than 25%) that depended on the postoperative lumbopelvic kinematics and preoperative L4-L5 disc condition. Postoperative alterations in adjacent disc shear, facet/ligament forces, and annulus stresses/strains were greater ( 25%) than those found in intradiscal pressure and compression ( 25%). Kinetics of the lower (L5-S1) and upper (L3-L4) adjacent segments were altered to different degrees.Alterations in segmental rotations mainly affected adjacent disc shear forces, facet/ligament forces, and annulus/collagen fibers stresses/strains. An altered lumbopelvic rhythm (increased pelvis rotation) tends to mitigate some of these surgically induced changes.

Background: Pedicle screw (PS) placement has been widely used in fusion surgeries on the thoracic spine. Achieving cost-effective yet accurate placements through nonradiation techniques remains challenging. Questions/Purposes: Novel noncovering lock-mechanism bilateral vertebra-specific drill guides for PS placement were designed/fabricated, and their accuracy for both nondeformed and deformed thoracic spines was tested. Methods: One nondeformed and 1 severe scoliosis human thoracic spine underwent computed tomographic (CT) scanning, and 2 identical proportions of each were 3-dimensional (3D) printed. Pedicle-specific optimal (no perforation) drilling trajectories were determined on the CT images based on the entry point/orientation/diameter/length of each PS. Vertebra-specific templates were designed and 3D printed, assuring minimal yet firm contacts with the vertebrae through a noncovering lock mechanism. One model of each patient was drilled using the freehand and one using the template guides (96 pedicle drillings). Postoperative CT scans from the models with the inserted PSs were obtained and superimposed on the preoperative planned models to evaluate deviations of the PSs. Results: All templates fitted their corresponding vertebra during the simulated operations. As compared with the freehand approach, PS placement deviations from their preplanned positions were significantly reduced: for the nonscoliosis model, from 2.4 to 0.9 mm for the entry point, 5.0° to 3.3° for the transverse plane angle, 7.1° to 2.2° for the sagittal plane angle, and 8.5° to 4.1° for the 3D angle, improving the success rate from 71.7% to 93.5%. Conclusions: These guides are valuable, as the accurate PS trajectory could be customized preoperatively to match the patients’ unique anatomy. In vivo studies will be required to validate this approach.

Spinal posture including thorax/pelvis orientations as well as loads on the intervertebral discs are crucial parameters in biomechanical models and ergonomics to evaluate the risk of low back injury. In vivo measurement of spinal posture toward estimation of spine loads requires the common motion capture techniques and laboratory instruments that are costly and time-consuming. Hence, a closed loop algorithm including an artificial neural network (ANN) and fuzzy logic is proposed here to predict the L5–S1 segment loads and thorax/pelvis orientations in various 3D reaching activities. Two parts namely a fuzzy logic strategy and an ANN from this algorithm; the former, developed based on the measured postures of 20 individuals, is to determine 3D orientations of the thorax/pelvis during the various activities while the latter, developed based on the predicted L5–S1 loads by a detailed musculoskeletal model of the spine, is to estimate compression/shear forces at the L5–S1 disc. The fuzzy logic rules are extracted based on Sugeno inference engine and the ANN is trained by LevenbergMarquardt algorithm. To evaluate the performance of the proposed strategy, the comparison between the predicted values, the target values and the presented values in the literature are reviewed. The comparison demonstrated that the proposed algorithm had a promising performance. The maximum relative error for all predictions was ~19 % and with respect to the target values while this error for the literature’s values was ~37 %. Also, the average improvement of the proposed strategy was ~17 % with respect to the presented strategy in the literature.

Conventional electromyography-driven (EMG) musculoskeletal models are calibrated during maximum voluntary contraction (MVC) tasks, but individuals with low back pain cannot perform unbiased MVCs. To address this issue, EMG-driven models can be calibrated in submaximal tasks. However, the effects of maximal (when data points include the maximum contraction) and submaximal calibration techniques on model outputs (e.g., muscle forces, spinal loads) remain yet unknown. We calibrated a subject-specific EMG-driven model, using maximal/submaximal isometric contractions, and simulated different independent tasks. Both approaches satisfactorily predicted external moments (Pearson's correlation ∼ 0.75; relative error = 44%), and removing calibration tasks under axial torques markedly improved the model performance (Pearson's correlation ∼ 0.92; relative error ∼ 28%). Unlike individual muscle forces, gross (aggregate) model outputs (i.e., spinal loads, stability index, and sum of abdominal/back muscle forces) estimated from maximal and submaximal calibration techniques were highly correlated (r 0.78). Submaximal calibration method overestimated spinal loads (6% in average) and abdominal muscle forces (11% in average). Individual muscle forces estimated from maximal and submaximal approaches were substantially different; however, gross model outputs (especially internal loads and stability index) remained highly correlated with small to moderate relative differences; therefore, the submaximal calibration technique can be considered as an alternative to the conventional maximal calibration approach.

Adjacent segment disorders are prevalent in patients following a spinal fusion surgery. Postoperative alterations in the adjacent segment biomechanics play a role in the etiology of these conditions. While experimental approaches fail to directly quantify spinal loads, previous modeling studies have numerous shortcomings when simulating the complex structures of the spine and the pre/postoperative mechanobiology of the patient. The biomechanical effects of the L4–L5 fusion surgery on muscle forces and adjacent segment kinetics (compression, shear, and moment) were investigated using a validated musculoskeletal model. The model was driven by in vivo kinematics for both preoperative (intact or severely degenerated L4–L5) and postoperative conditions while accounting for muscle atrophies. Results indicated marked changes in the kinetics of adjacent L3–L4 and L5–S1 segments (e.g., by up to 115% and 73% in shear loads and passive moments, respectively) that depended on the preoperative L4–L5 disc condition, postoperative lumbopelvic kinematics and, to a lesser extent, postoperative changes in the L4–L5 segmental lordosis and muscle injuries. Upper adjacent segment was more affected post-fusion than the lower one. While these findings identify risk factors for adjacent segment disorders, they indicate that surgical and postoperative rehabilitation interventions should focus on the preservation/restoration of patient’s normal segmental kinematics.

Objective Spine kinematics, kinetics, and trunk muscle activities were evaluated during different stages of a fatigue-induced symmetric lifting task over time. Background Due to neuromuscular adaptations, postural behaviors of workers during lifting tasks are affected by fatigue. Comprehensive aspects of these adaptations remain to be investigated. Method Eighteen volunteers repeatedly lifted a box until perceived exhaustion. Body center of mass (CoM), trunk and box kinematics, and feet center of pressure (CoP) were estimated by a motion capture system and force-plate. Electromyographic (EMG) signals of trunk/abdominal muscles were assessed using linear and nonlinear approaches. The L5-S1 compressive force (Fc) was predicted via a biomechanical model. A two-way multivariate analysis of variance (MANOVA) was performed to examine the effects of five blocks of lifting cycle (C1 to C5) and lifting trial (T1 to T5), as independent variables, on kinematic, kinetic, and EMG-related measures. Results Significant effects of lifting trial blocks were found for CoM and CoP shift in the anterior–posterior direction (respectively p < .001 and p = .014), trunk angle ( p = .004), vertical box displacement ( p < .001), and Fc ( p = .005). EMG parameters indicated muscular fatigue with the extent of changes being muscle-specific. Conclusion Results emphasized variations in most kinematics/kinetics, and EMG-based indices, which further provided insight into the lifting behavior adaptations under dynamic fatiguing conditions. Application Movement and muscle-related variables, to a large extent, determine the magnitude of spinal loading, which is associated with low back pain.

Measurements of spinal segment ranges of motion (RoMs), movement coordination, and three-dimensional kinematics during occupational activities have implications in occupational/clinical biomechanics. Due to the large amount of adipose tissues, obese individuals may have different RoMs, lumbopelvic coordination, and kinematics than normal-weight ones. We aimed to measure/compare trunk, lumbar, and pelvis primary RoMs in all anatomical planes/directions, lumbopelvic ratios (lumbar to pelvis rotations at different trunk angles) in all anatomical planes/directions and three-dimensional spine kinematics during twelve symmetric/asymmetric statics load-handling activities in healthy normal-weight and obese individuals. Kinematics/motion data were collected from nine healthy young male normal-weight and nine age/height/sex matched obese individuals via a ten-camera Vicon motion capture system. Obese individuals had significantly smaller (p 0.05) lumbar flexion (~9° in average) and larger pelvis right lateral bending (~5°) RoMs as well as smaller lumbopelvic ratios (~37%) in lateral bending and axial rotation movements as compared to normal-weight individuals. Moreover, the two groups had generally non-significant different segmental orientations (20° and in most cases 10°) in load-handling tasks that depended on the magnitude of load asymmetry angle (p 0.05). Differences were larger for tasks performed near the floor, away from body, and at larger load asymmetry angles. Biomechanical models simulating pure lateral bending, axial rotation, or tasks involving large load asymmetry may therefore need subject-specific, rather than population-based, motion analysis due to the effects from body weight. In clinical applications, it should be noted that healthy obese individuals may have different RoMs and lumbopelvic rhythms than healthy normal-weight individuals in some anatomical planes/directions.

Low back pain and spinal disorders caused by whole-body vibration (WBV) are almost common in industrial machine operators' society, especially forklift operators. In this study, WBV was studied while operators were performing their assigned tasks. Moreover, the effect of awkward static posture was separately investigated. Results revealed that the risk of injury caused by WBV at higher speeds and heavier loads is extremely high and some actions should be taken in order to guard against probable disorders in the operators. Accordingly, several interventions were proposed; for instance, reducing the speed of the forklifts and using air cushions on the seats can reduce the injury risk remarkably.

Spinal fusion surgery is usually followed by accelerated degenerative changes in the unfused segments above and below the treated segment(s), i.e., adjacent segment disease (ASD). While a number of risk factors for ASD have been suggested, its exact pathogenesis remains to be identified. Finite element (FE) models are indispensable tools to investigate mechanical effects of fusion surgeries on post-fusion changes in the adjacent segment kinematics and kinetics. Existing modeling studies validate only their intact FE model against in vitro data and subsequently simulate post-fusion in vivo conditions. The present study provides a novel approach for the comprehensive validation of a lumbar (T12-S1) FE model in post-fusion conditions. Sixteen simulated fusion surgeries, performed on cadaveric specimens using various testing and loading conditions, were modeled by this FE model. Predictions for adjacent segment range of motion (RoM) and intradiscal pressure (IDP) were compared with those obtained from the corresponding in vitro tests. Overall, 70% of the predicted adjacent segment RoMs were within the range of in vitro data for both intact and post-fusion conditions. Correlation (r) values between model and in vitro findings for the adjacent segment RoMs were positive and greater than 0.84. Most of the predicted IDPs were, however, out of the narrow range of in vitro IDPs at the adjacent segments but with great positive correlations (r ≥ 0.89). FE modeling studies investigating the effect of fusion surgery on in vivo adjacent segment biomechanics are encouraged to use post-surgery in vitro data to validate their FE model.

Low back pain (LBP), the leading cause of disability worldwide, remains one of the most common and challenging problems in occupational musculoskeletal disorders. The effective assessment of LBP injury risk, and the design of appropriate treatment modalities and rehabilitation protocols, require accurate estimation of the mechanical spinal loads during different activities. This study aimed to: (1) develop a novel 2D beam-column finite element control-based model of the lumbar spine and compare its predictions for muscle forces and spinal loads to those resulting from a geometrically matched equilibrium-based model; (2) test, using the foregoing control-based finite element model, the validity of the follower load (FL) concept suggested in the geometrically matched model; and (3) investigate the effect of change in the magnitude of the external load on trunk muscle activation patterns. A simple 2D continuous beam-column model of the human lumbar spine, incorporating five pairs of Hill’s muscle models, was developed in the frontal plane. Bio-inspired fuzzy neuro-controllers were used to maintain a laterally bent posture under five different external loading conditions. Muscle forces were assigned based on minimizing the kinematic error between target and actual postures, while imposing a penalty on muscular activation levels. As compared to the geometrically matched model, our control-based model predicted similar patterns for muscle forces, but at considerably lower values. Moreover, irrespective of the external loading conditions, a near (

Excessive loads on the human spine is recognized as a risk factor for back injuries/pain. Various lifting analysis tools such as musculoskeletal models, regression equations and NIOSH (National Institute for Occupational Safety and Health) lifting equation (NLE) have been proposed to evaluate and mitigate associated risks during manual material handling activities. Present study aims to compare predicted spinal loads from 5 different lifting analysis tools as well as to critically evaluate the NIOSH recommended weight limit (RWL). Spinal loads were estimated under different symmetric/asymmetric lifting tasks in which hand-load mass at each task was set based on RWL from NLE. Estimated intradiscal pressures (IDPs) of various tools were also compared with in vivo measurements. We compared RWL by NLE versus our estimations of RWL calculated from our regression equations using biomechanical criteria (compression3400 N with/without shear1000, 1250 or 1500 N). Our regression equations followed by OpenSim, AnyBody, simple polynomial and 3DSSPP satisfactorily predicted L4-L5 IDPs. Lifting analysis tools estimated comparable spinal compression forces (mean Pearson's r = 0.80; standard deviation of relative difference = 26%) while in shear, differences were greater (mean Pearson's r = 0.68; standard deviation of relative difference = 56%). NLE estimations of RWL were conservative in comparison with our estimations for lean individuals (BMI 25 kg/m

Traditional electromyography-assisted optimization (TEMG) models are commonly employed to compute trunk muscle forces and spinal loads for the design of clinical/treatment and ergonomics/prevention programs. These models calculate muscle forces solely based on moment equilibrium requirements at spinal joints. Due to simplifications/assumptions in the measurement/processing of surface EMG activities and in the presumed muscle EMG-force relationship, these models fail to satisfy stability requirements. Hence, the present study aimed to develop a novel stability-based EMG-assisted optimization (SEMG) method applied to a musculoskeletal spine model in which trunk muscle forces were estimated by enforcing equilibrium conditions constrained to stability requirements. That is, second-order partial derivatives of the potential energy of the musculoskeletal model with respect to its generalized coordinates were enforced to be positive semi-definite. Fifteen static tasks in upright and flexed postures with and without a hand load at different heights were simulated. The SEMG model predicted different muscle recruitments/forces (generally larger global and local muscle forces) and spinal loads (slightly larger) compared to the TEMG model. Such task-specific differences were dependant on the assumed magnitude of the muscle stiffness coefficient in the SEMG model. The SEMG model-predicted and measured L4-L5 intradiscal pressures were in satisfactory agreement during simulated activities.

Maximum voluntary exertion (MVE) tasks quantify trunk strength and maximal muscle electromyography (EMG) activities with both clinical and biomechanical implications. The aims here are to evaluate the performance of an existing trunk musculoskeletal model, estimate maximum muscle stresses and spinal forces, and explore likely differences between males and females in maximum voluntary exertions. We, therefore, measured trunk strength and EMG activities of 19 healthy right-handed subjects (9 females and 10 males) in flexion, extension, lateral and axial directions. MVEs for all subjects were then simulated in a subject-specific trunk musculoskeletal model, and estimated muscle activities were compared with EMGs. Analysis of variance was used to compare measured moments and estimated spinal loads at the L5-S1 level between females and males. MVE moments in both sexes were greatest in extension (means of 236 Nm in males and 190 Nm in females) and least in left axial torque (97 Nm in males and 64 Nm in females). Being much greater in lateral and axial MVEs, coupled moments reached ∼50% of primary moments in average. Females exerted less moments in all directions reaching significance except in flexion. Muscle activity estimations were strongly correlated with measurements in flexion and extension (Pearson’s r = 0.69 and 0.76), but the correlations were very weak in lateral and axial MVEs (Pearson’s r = 0.27 and 0.13). Maximum muscle stress was in average 0.80 ± 0.42 MPa but varied among muscles from 0.40 ± 0.22 MPa in rectus abdominis to 0.99 ± 0.29 MPa in external oblique. To estimate maximum muscle stresses and evaluate validity of a musculoskeletal model, MVEs in all directions with all coupled moments should be considered.

Evaluation of spinal range of motions (RoMs) and movement coordination between its segments (thorax, lumbar, and pelvis) has clinical and biomechanical implications. Previous studies have not recorded three-dimensional primary/coupled motions of all spinal segments simultaneously. Moreover, magnitude/direction of the coupled motions of the thorax/pelvis in standing posture and lumbopelvic rhythms in the frontal/transverse planes have not been investigated. This study, hence, used an inertial tracking device to measure T1, T5, T12, total (T1-T12) thoracic, lower (T5-T12) and upper (T1-T5) thoracic, lumbar (T12-S1), and pelvis primary and coupled RoMs as well as their movement coordination in all anatomical planes/directions in twenty-two healthy individuals. RoMs were statistically compared between the anatomical planes and spinal segments as well as with available data in the literature. The spine had different primary RoMs in different planes/directions (flexion: lumbar: 55.4 ± 12.4°, pelvis: 42.8 ± 21.6°, and T1-T12 thoracic: 19.9 ± 6.4°, extension: lumbar: 23.4 ± 10.1°, thoracic: 11.7 ± 3.4°, and pelvis: 10.2 ± 6.4°, left/right lateral bending: thoracic: 24.5 ± 7.4°/26.5 ± 6.1°, lumbar: 16.4 ± 7.2°/18.3 ± 5.7°, and pelvis: 11.0 ± 4.4°/9.3 ± 6.2°, and left/right axial rotation: thoracic: 33.5 ± 10.0°/37.1 ± 11.7°, pelvis: 31.6 ± 12.5°/27.2 ± 12.0° and lumbar: 7.5 ± 4.5°/9.2 ± 7.3°). Pelvis, lumbar and thoracic spine had different/varying contributions/rhythms to generate total trunk (T1) movement, both within and between planes. Pattern of the coupled motions was inconsistent between subjects but side bending was generally associated with twisting to the same side at the thoracic spine and to the opposite side at the lumbar spine.

Epidemiological studies have identified obesity asa possible risk factor for low back disorders. Biomechanical models can help test such hypothesis and shed light on the mechanism involved. A novel subject-specific musculoskeletal-modelling approach is introduced to estimate spinal loads during static activities in five healthy obese (BMI>30kg/m2) and five normal-weight (20 0.05). Heavier subjects did not necessarily have larger muscle moment arms (e.g., they were larger in 64kg (BMI=20.7kg/m2) subject than 78kg (BMI=24.6kg/m2) subject) or greater T1-L5 trunk weight (e.g., the 97kg (BMI=31kg/m2) subject had similar trunk weight as 109kg (BMI=33.3kg/m2) subject). Obese individuals had in average greater spinal loads than normal-weight ones but heavier subjects did not necessarily have greater spinal loads (117kg (BMI=40.0kg/m2) subject had rather similar L5-S1 compression as 105kg (BMI=34.7kg/m2) subject). Predicted L4-L5 intradiscal pressures for the normal-weight subjects ranged close to the measured values (R2=0.85-0.92). Obese individuals did not necessarily have greater IDPs than normal-weight ones.

Body posture measurement approaches, required in biomechanical models to assess risk of musculoskeletal injuries, are usually costly and/or impractical for use in real workplaces. Therefore, we recently developed three artificial neural networks (ANNs), based on measured posture data on several individuals, to predict whole body 3D posture (coordinates of 15 markers located on body's main joints), segmental orientations (Euler angles of 14 body segments), and lumbosacral (L5-S1) moments during static manual material handling (MMH) activities (ANN

Background Motor control exercise was claimed to improve spinal stability in patients with chronic non-specific back pain, but to investigate the effectiveness of this exercise, other outcome measures have been used rather than spinal stability itself. The aim of our study is to assess motor control exercise effects on spinal stability using a biomechanical model. Methods Fifty-one patients were assigned to either motor control or general exercises. Before and after trainings, participants were tested for spinal stability at seven isometric tasks. Electromyography signals were recorded from ten superficial muscles, and a hybrid EMG-driven musculoskeletal model estimated spinal stability indices at each task. Findings Pain and disability significantly decreased in both groups. After trainings, patients had both increase and decrease in stability depending on the task, and stability did not increase/decrease uniformly in all patients. In the motor control group, stability increased at all positions but reached to significance only at right lateral pulling. In the general exercise group, except for pulling the trunk backward, stability decreased at other positions and reached to statistical significance only at pulling the trunk forward. No significant difference between groups was found in changing stability after the intervention. Interpretation Interventions yielded no significant difference in disability, pain and stability index between two groups. Significant increase of stability in the motor control group at right lateral pulling may be attributed to more activity of abdominal muscles, and significant decrease of stability in the general exercise group at forward pulling may be attributed to more optimal activity of back muscles.

Underlying mechanisms of obesity-related back pain remain unexplored. Thus, we aim to determine the effect of obesity and its shapes on the spinal loads and the associated risks of injury. Obesity shapes were initially constructed by principal component analysis based on datasets on 5852 obese individuals. Spinal loads, cycles to vertebral failure and trunk stability margin were estimated in a subject-specific trunk model taking account of personalized musculature, passive ligamentous spine, obesity shapes, segmental weights, spine kinematics and bone mineral density. Three obesity shapes (mean and extreme abdominal circumferences) at three body weights (BWs) of 86, 98 and 109 kg were analyzed. Additional BW (12 kg) increased spinal loads by ~11.8%. Higher waist circumferences at identical BW increased spinal forces to the tune of ~20 kg additional BW and the risk of vertebral fatigue compression fracture by 3-7 times when compared with smaller waist circumferences. Forward flexion, greater BW and load in hands increased the trunk stability margin. Spinal loads markedly increased with BW, especially at greater waist circumferences. The risk of vertebral fatigue fracture also substantially increased at greater waist circumferences though not at smaller ones. Obesity and its shape should be considered in spine biomechanics.

An essential input to the musculoskeletal (MS) trunk models that estimate muscle and spine forces is kinematics of the thorax, pelvis, and lumbar vertebrae. While thorax and pelvis kinematics are usually measured via skin motion capture devices (with inherent errors on the proper identification of the underlying bony landmarks and the relative skin-sensor-bone movements), those of the intervening lumbar vertebrae are commonly approximated at fixed proportions based on the thorax-pelvis kinematics. This study proposes an image-based kinematics measurement approach to drive subject-specific (musculature, geometry, mass, and center of masses) MS models. Kinematics of the thorax, pelvis, and individual lumbar vertebrae as well as disc inclinations, gravity loading, and musculature were all measured via different imaging techniques. The model estimated muscle and lumbar forces in various upright and flexed postures in which kinematics were obtained using upright fluoroscopy via 2D/3D image registration. Predictions of this novel image-kinematics-driven model (Img-KD) were compared with those of the traditional kinematics-driven (T-KD) model in which individual lumbar vertebral rotations were assumed based on thorax-pelvis orientations. Results indicated that while differences between Img-KD and T-KD models remained small for the force in the global muscles (attached to the thoracic cage) (

Irrespective of the lifting technique (squat or stoop), the lumbar spine posture (more kyphotic versus more lordotic) adopted during lifting activities is an important parameter affecting the active-passive spinal load distribution. The advantages in either posture while lifting remains, however, a matter of debate. To comprehensively investigate the role on the trunk biomechanics of changes in the lumbar posture (lordotic, free or kyphotic) during forward trunk flexion, validated musculoskeletal and finite element models, driven by in vivo kinematics data, were used to estimate detailed internal tissue stresses-forces in and load-sharing among various joint active-passive tissues. Findings indicated that the lordotic posture, as compared to the kyphotic one, resulted in marked increases in back global muscle activities (~14–19%), overall segmental compression (~7.5–46.1%) and shear (~5.4–47.5%) forces, and L5-S1 facet joint forces (by up to 80 N). At the L5-S1 level, the lordotic lumbar posture caused considerable decreases in the moment resisted by passive structures (spine and musculature, ~14–27%), negligible reductions in the maximum disc fiber strains (by ~0.4–4.7%) and small increases in intradiscal pressure (~1.8–3.4%). Collectively and with due consideration of the risk of fatigue and viscoelastic creep especially under repetitive lifts, current results support a free posture (in between the extreme kyphotic and lordotic postures) with moderate contributions from both active and passive structures during lifting activities involving trunk forward flexion.

Spine musculoskeletal (MS) models make simplifying assumptions on the intervertebral joint degrees-of-freedom (rotational and/or translational), representation (spherical or beam-like joints), and properties (linear or nonlinear). They also generally neglect the realistic structure of the joints with disc nuclei/annuli, facets, and ligaments. We aim to develop a novel MS model where trunk muscles are incorporated into a detailed finite element (FE) model of the ligamentous T12-S1 spine thus constructing a gold standard coupled MS-FE model. Model predictions are compared under some tasks with those of our earlier spherical joints, beam joints, and hybrid (uncoupled) MS-FE models. The coupled model predicted L4-L5 intradiscal pressures (R2 ≅ 0.97, RMSE ≅ 0.27 MPa) and L1-S1 centers of rotation (CoRs) in agreement to in vivo data. Differences in model predictions grew at larger trunk flexion angles; at the peak (80°) flexion the coupled model predicted, compared to the hybrid model, much smaller global/local muscle forces (~38%), segmental (~44%) and disc (~22%) compression forces but larger segmental (~9%) and disc (~17%) shear loads, ligament forces at the lower lumbar levels (by up to 57%) and facet forces at all levels. The spherical/beam joints models predicted much greater muscle forces and segmental loads under larger flexion angles. Unlike the spherical joints model with fixed CoRs, the beam joints model predicted CoRs closer (RMSE = 2.3 mm in flexion tasks) to those of the coupled model. The coupled model offers a great potential for future studies towards improvement of surgical techniques, management of musculoskeletal injuries and subject-specific simulations.

A number of musculoskeletal models of the human spine have been used for predictions of lumbar and muscle forces. However, the predictive power of these models might be limited by a commonly made assumption; thoracic region is represented as a single lumped rigid body. This study hence aims to investigate the impact of such assumption on the predictions of spinal and muscle forces. A validated thoracolumbar spine model was used with a flexible thorax (T1–T12), a completely rigid one or rigid with thoracic posture updated at each analysis step. The simulations of isometric forward flexion up to 80°, with and without a 20 kg hand load, were performed, based on the previously measured kinematics. Depending on the simulated task, the rigid model predicted slightly or moderately lower compressive loading than the flexible one. The differences were relatively greater at the upper lumbar levels (average underestimation of 14% at the T12L1 for flexion tasks and of 18% for flexion tasks with hand load) as compared to the lower levels (3% and 8% at the L5S1 for unloaded and loaded tasks, respectively). The rigid model with updated thoracic posture predicted compressive forces similar to those of the rigid model. Predicted muscle forces were, however, very different between the three models. This study indicates that the lumbar spine models with a rigid thorax definition can be used for loading investigations at the lowermost spinal levels. For predictions of upper lumbar spine loading, using models with an articulated thorax is advised.

Development of a subject-specific computational musculoskeletal trunk model (accounting for age, sex, body weight and body height), estimation of muscle forces and internal loads as well as subsequent validation by comparison with measured intradiscal pressure in various lifting tasks are novel, important and challenging. The objective of the present study is twofold. First, it aims to update and personalize the passive and active structures in an existing musculoskeletal kinematics-driven finite element model. The scaling scheme used an existing imaging database and biomechanical principles to adjust muscle geometries/cross-sectional-areas and passive joint geometry/properties in accordance with subjects' sex, age, body weight and body height. Second, using predictions of a detailed passive finite element model of the ligamentous lumbar spine, a novel nonlinear regression equation was proposed that relates the intradiscal pressure (IDP) at the L4-L5 disc to its compression force and intersegmental flexion rotation. Predicted IDPs and muscle activities of the personalized models under various tasks are found in good-to-excellent agreement with reported measurements. Results indicate the importance of personal parameters when computing muscle forces and spinal loads especially at larger trunk flexion angles as minor changes in individual parameters yielded up to 30 % differences in spinal forces. For more accurate subject-specific estimation of spinal loads and muscle activities, such a comprehensive trunk model should be used that accounts for subject's personalized features on active musculature and passive spinal structure.

Range of motion (ROM) of the thoracic spine has implications in patient discrimination for diagnostic purposes and in biomechanical models for predictions of spinal loads. Few previous studies have reported quite different thoracic ROMs. Total (T1-T12), lower (T5-T12) and upper (T1-T5) thoracic, lumbar (T12-S1), pelvis, and entire trunk (T1) ROMs were measured using an inertial tracking device as asymptomatic subjects flexed forward from their neutral upright position to full forward flexion. Correlations between body height and the ROMs were conducted. An effect of measurement errors of the trunk flexion (T1) on the model-predicted spinal loads was investigated. Mean of peak voluntary total flexion of trunk (T1) was 118.4 ± 13.9°, of which 20.5 ± 6.5° was generated by flexion of the T1 to T12 (thoracic ROM), and the remaining by flexion of the T12 to S1 (lumbar ROM) (50.2 ± 7.0°) and pelvis (47.8 ± 6.9°). Lower thoracic ROM was significantly larger than upper thoracic ROM (14.8 ± 5.4° versus 5.8 ± 3.1°). There were non-significant weak correlations between body height and the ROMs. Contribution of the pelvis to generate the total trunk flexion increased from ~20% to 40% and that of the lumbar decreased from ~60% to 42% as subjects flexed forward from upright to maximal flexion while that of the thoracic spine remained almost constant (~16% to 20%) during the entire movement. Small uncertainties (±5°) in the measurement of trunk flexion angle resulted in considerable errors (~27%) in the model-predicted spinal loads only in activities involving small trunk flexion.

A hallmark of more advanced models is their higher details of trunk muscles represented by a larger number of muscles. The question is if in reality we control these muscles individually as independent agents or we control groups of them called "synergy". To address this, we employed a 3-D biomechanical model of the spine with 18 trunk muscles that satisfied equilibrium conditions at L4/5, with different cost functions. The solutions of several 2-D and 3-D tasks were arranged in a data matrix and the synergies were computed by using non-negative matrix factorization (NMF) algorithms. Variance accounted for (VAF) was used to evaluate the number of synergies that emerged by the analysis, which were used to reconstruct the original muscle activations. It was showed that four and six muscle synergies were adequate to reconstruct the input data of 2-D and 3-D torque space analysis. The synergies were different by choosing alternative cost functions as expected. The constraints affected the extracted muscle synergies, particularly muscles that participated in more than one functional tasks were influenced substantially. The compositions of extracted muscle synergies were in agreement with experimental studies on healthy participants. The following computational methods show that the synergies can reduce the complexity of load distributions and allow reduced dimensional space to be used in clinical settings.

Spinal loads are recognized to play a causative role in back disorders and pain. Knowledge of lumbar spinal loads is required in proper management of various spinal disorders, effective risk prevention and assessment in the workplace, sports and rehabilitation, realistic testing of spinal implants as well as adequate loading in in vitro studies. During the last few decades, researchers have used a number of techniques to estimate spinal loads by measuring in vivo changes in the intradiscal pressure, body height, or forces and moments transmitted via instrumented vertebral implants. In parallel, computational models have been employed to estimate muscle forces and spinal loads under various static and dynamic conditions. Noteworthy is the increasing growth in latter computational investigations. This paper aims to review, compare and critically evaluate the existing literature on in vivo measurements and computational model studies of lumbar spinal loads to lay the foundation for future biomechanical studies. Towards this goal, the paper reviews in separate sections models dealing with static postures (standing, sitting, lying) as well as slow and fast dynamic activities (lifting, sudden perturbations and vibrations). The findings are helpful in many areas such as work place safety design and ergonomics, injury prevention, performance enhancement, implant design and rehabilitation management.

Evaluation of workers’ body posture in workstations is a prerequisite to estimate spinal loads and assess risk of injury for the subsequent design of preventive interventions. The Microsoft Kinect™ sensor is, in this regard, advantageous over the traditional skin-marker-based optical motion capture systems for being marker-less, portable, cost-effective, and easy-to-use in real workplaces. While several studies have demonstrated the validity/reliability of the Kinect for posture measurements especially during gait trials, its capability to adequately drive a detailed spine musculoskeletal model for injury risk assessments remains to be investigated. Lumbosacral (L5-S1) load predictions of a Kinect-driven and a gold-standard marker-based Vicon-driven musculoskeletal model were compared for various standing static load-handling activities at different heights/asymmetry angles/distances. Full body kinematics of eight individuals each performing eighteen activities were simultaneously recorded by a single-front-placed Kinect and a 10-camera Vicon motion capture system and input to AnyBody Modeling System. The predicted spinal loads by the two models were in average different by 17.8 and 25.9% for the L5-S1 disc compressive and shear forces, respectively, with smaller errors for the activities at higher load heights. Some activities performed near the floor could, however, not be recorded by a single-front-placed Kinect sensor due to the joint occlusion. The capability of the Kinect to adequately drive a spine musculoskeletal model depended on the complexity of the activity. While a single front-placed Kinect camera can be used to evaluate spinal loads in a wide range of static/quasi-static activities, cautious should be exercised when evaluating tasks performed near the floor.

Workplace safety assessment, personalized treatment design and back pain prevention programs require accurate subject-specific estimation of spinal loads. Since no noninvasive method can directly estimate spinal loads, easy-to-use regression equations that are constructed based on the results of complex musculoskeletal models appear as viable alternatives. Thus, we aim to develop subject-specific regression equations of L4-L5 and L5-S1 shear and compression forces during various symmetric/asymmetric tasks using a nonlinear personalized finite element musculoskeletal trunk model. Kinematics and electromyography (EMG) activities of 19 young healthy subjects were collected during 64 different symmetric/asymmetric tasks. To investigate the reliability and accuracy of the musculoskeletal model and regression equations, we compared estimated trunk muscle activities and L4-L5 intradiscal pressures (IDPs) respectively with our own electromyography data (EMGs) and reported in vivo pressure measurements. Although in general, six independent rotation components (three trunk T11 rotations and three pelvic S1 rotations) are required to determine kinematics along the spine, only two surrogate variables (trunk flexion and its asymmetric angles) satisfactorily predicted all six rotation components (R2 > 0.94). Regression equations, developed based on subject-specific inputs, predicted spinal loads in satisfactory agreement with IDP measurements (R2 = 0.85). Predicted muscle activities in the personalized musculoskeletal models were in moderate to weak agreements with our measured EMGs in 19 participants. Based on dominance analysis, trunk flexion and its asymmetry angle, hand-load weight, hand-load lever arm, and body weight were the most important variables while the effects of body height and sex on spinal loads remained small.

Biomechanical modeling approaches require body posture to evaluate the risk of spine injury during manual material handling. The procedure to measure body posture via motion-analysis techniques as well as the subsequent calculations of lumbosacral moments and spine loads by, respectively, inverse-dynamic and musculoskeletal models are complex and time-consuming. We aim to develop easy-to-use yet accurate artificial neural networks (ANNs) that predict 3D whole-body posture (ANNposture), segmental orientations (ANNangle), and lumbosacral moments (ANNmoment) based on our measurements during load-handling activities. Fifteen individuals each performed 135 load-handling activities by reaching (0 kg) or handling (5 and 10 kg) weights located at nine different horizontal and five vertical (0, 30, 60, 90, and 120 cm from the floor) locations. Whole-body posture was measured via a motion capture system and lumbosacral moments were calculated via a 3D top-down eight link-segment inverse-dynamic model. ANNposture, ANNangle, and ANNmoment were trained (RMSEs = 6.7 cm, 29.8°, and 16.2 Nm, respectively) and their generalization capability was tested (RMSE = 7.0 cm and R2 = 0.97, RMSE = 29.9° and R2 = 0.85, and RMSE = 16.5 Nm and R2 = 0.97, respectively). These ANNs were subsequently coupled to our previously-developed/validated ANNload, which predicts spinal loads during 3D load-handling activities. The results showed outputs of the coupled ANNs for L4-L5 intradiscal pressure (IDPs) during a number of activities were in agreement with measured IDPs (RMSE = 0.37 MPa and R2 = 0.89). Hence, coupled ANNs were found to be robust tools to evaluate posture, lumbosacral moments, spinal loads, and thus risk of injury during load-handling activities.

Recent advances in medical imaging techniques have allowed pure displacement-control trunk models to estimate spinal loads with no need to calculate muscle forces. Sensitivity of these models to the errors in post-imaging evaluation of displacements (reported to be ∼0.4–0.9° and 0.2–0.3 mm in vertebral displacements) has not yet been investigated. A Monte Carlo analysis was therefore used to assess the sensitivity of results in both musculoskeletal (MS) and passive finite element (FE) spine models to errors in measured displacements. Six static activities in upright standing, flexed, and extended postures were initially simulated using a force-control hybrid MS-FE model. Computed vertebral displacements were subsequently used to drive two distinct fully displacement-control MS and FE models. Effects of alterations in the reference vertebral displacements (at 3 error levels with SD (standard deviation) = 0.1, 0.2, and 0.3 mm in input translations together with, respectively, 0.2, 0.4, and 0.6° in input rotations) were investigated on the model predictions. Results indicated that outputs of both models had substantial task-dependent sensitivities to errors in the measured vertebral translations. For instance, L5-S1 intradiscal pressures (IDPs) were considerably affected (SD values reaching 1.05 MPa) and axial compression and shear forces even reversed directions as translation errors increased to 0.3 mm. Outputs were however generally much less sensitive to errors in measured vertebral rotations. Accounting for the accuracies in image-based kinematics measurements, therefore, it is concluded that the current measured vertebral translation errors at and beyond 0.1 mm are too large to drive biomechanical models of the spine.

Objective:To assess adequacy of the National Institute for Occupational Safety and Health (NIOSH) Lifting Equation (NLE) in controlling lumbar spine loads below their recommended action limits during asymmetric load-handling activities using a detailed musculoskeletal model, that is, the AnyBody Modeling System.Background:The NIOSH committee employed simplistic biomechanical models for the calculation of the spine compressive loads with no estimates of the shear loads. It is therefore unknown whether the NLE would adequately control lumbar compression and shear loads below their recommended action limits during asymmetric load-handling activities.Method:Twenty-four static stoop lifting tasks at different load asymmetry angles, heights, and horizontal distances were performed by one normal-weight (70 kg) and one obese (93 kg) individual. For each task, the recommended weight limit computed by the NLE and body segment angles measured by a video-camera system (VICON) were prescribed in the participant-specific models developed in the AnyBody Modeling System that estimated spinal loads.Results:For both individuals, the NLE adequately controlled L5-S1 loads below their recommended action limits for all activities performed in upright postures. Both individuals, however, experienced compressive and/or shear L5-S1 loads beyond the recommended action limits when lifting was performed near the floor with large load asymmetry.Conclusion:The NLE failed to control spinal loads below the recommended limits during asymmetric lifting tasks performed near the floor.Application:The NLE should be used with caution for extreme tasks involving load handling near the floor with large load asymmetry.

Traditional load-control musculoskeletal and finite element (FE) models of the spine fail to accurately predict in vivo intervertebral joint loads due mainly to the simplifications and assumptions when estimating redundant trunk muscle forces. An alternative powerful protocol that bypasses the calculation of muscle forces is to drive the detailed FE models by image-based in vivo displacements. Development of subject-specific models, however, both involves the risk of extensive radiation exposures while imaging in supine and upright postures and is time consuming in terms of the reconstruction of the vertebrae, discs, ligaments, and facets geometries. This study therefore aimed to introduce a remedy for the development of subject-specific FE models by scaling the geometry of an existing detailed FE model of the T12-S1 lumbar spine. Five subject-specific scaled models were driven by their own radiography image-based displacements in order to predict joint loads, ligament forces, facet joint forces, and disc fiber strains during relaxed upright as well as moderate flexion and extension tasks. The predicted intradiscal pressures were found in adequate agreement with in vivo data for upright, flexion, and extension tasks. There were however large intersubject variations in the estimated joint loads and facet forces.

Low back pain is the most prevalent orthopedic disorder and the first main cause of poor working functionality in developed as wells as many developing countries. In Absence of noninvasive in vivo measurement approaches, biomechanical models are used to estimate mechanical loads on human joints during physical activities. To estimate joint loads via musculoskeletal models, the calculation of muscle forces are of importance. It is however difficult to estimate muscle forces as the number of muscles, i.e. unknown parameters, is far more than the existing degrees of freedom; the system is highly redundant. Therefore, in this study, instead of muscle forces estimation, their effects (i.e., rotations and displacements) is measured by medical imaging techniques and prescribed to a detailed finite element model of the L4-L5 spine segment to determine intervertebral disc pressure as a representative of compressive forces acting on the joint. A previously validated geometrically-detailed passive finite element model of the L4-L5 segment was used. Disc, facet joints, vertebrae, and ligaments were simulated with appropriate elements/material properties. Rotations and displacements of the L4 and L5 vertebrae from supine to upright and from upright to trunk flexion of 10° were measured via X-ray imaging. The kinematics were prescribed to the L4 and L5 centroids. Maximal intradiscal pressure of ~0.45 MPa was predicted for the simulated tasks that was in agreement with in vivo data in the literature. Preliminary results indicate feasibility of this kinematics-based approach to predict in vivo spine loads.

Previous studies have measured thoracic range of motion (RoM) using either skin-mounted devices or supine CT-imaging and have reported quite different RoMs. Given the inherent shortcomings of measurements of vertebrae movements from the overlying skin, the present study aims to measure normal RoM of the thoracic spine in the sagittal plane using the upright digital radiography. Lateral radiographs of the thoracic spine were acquired from eight asymptomatic male subjects in upright standing and full forward flexion using a mobile U-arm digital radiographic system. Total (T1-T12), upper (T1-T6), and lower (T6-T12) thoracic RoMs were measured. A throughout comparison with available skin-based measurements in the literature was carried out. Mean of total (T1-T12) thoracic RoM was 22.5° (SD 4.1°), most of which was generated by the lower (T6-T12) as compared to upper (T1-T6) thoracic spine (15.5° versus 7.1°, p measurements suffer from the inter sensor-skin-vertebra movements and supine imaging techniques do not allow maximal trunk flexion, standing radiography remains as the gold-standard technique. Evaluation of thoracic spine RoM has implications in both patient discrimination for diagnosis and in biomechanical models for estimation of spinal loads