M. Parnianpour

Predictive equations to estimate spinal loads in symmetric lifting tasks

Response surface methodology is used to establish robust and user-friendly predictive equations that relate responses of a complex detailed trunk finite element biomechanical model to its input variables during sagittal symmetric static lifting activities. Four input variables (thorax flexion angle, lumbar/pelvis ratio, load magnitude, and load position) and four model responses (L4-L5 and L5-S1 disc compression and anterior-posterior shear forces) are considered. Full factorial design of experiments accounting for all combinations of input levels is employed. Quadratic predictive equations for the spinal loads at the L4-S1 disc mid-heights are obtained by regression analysis with adequate goodness-of-fit (R(2)>98%, p<0.05, and low root-mean-squared-error values compared with the range of predicted spine loads). Results indicate that intradiscal pressure values at the L4-L5 disc estimated based on the predictive equations are in close agreement with available in vivo data measured under similar loadings and postures. Combinations of input (posture and loading) variable levels that yield spine loads beyond the tolerance compression limit of 3400 N are identified using contour plots. Ergonomists and bioengineers, faced with the dilemma of using either complex but more accurate models on one hand or less accurate but simple models on the other hand, have thereby easy-to-use predictive equations that quantifies spinal loads and risk of injury under different occupational tasks of interest.

Lumbopelvic rhythm during forward and backward sagittal trunk rotations: Combined in vivo measurement with inertial tracking device and biomechanical modeling

BACKGROUND The ratio of total lumbar rotation over pelvic rotation (lumbopelvic rhythm) during trunk sagittal movement is essential to evaluate spinal loads and discriminate between low back pain and asymptomatic population. METHODS Angular rotations of the pelvis and lumbar spine as well as their sagittal rhythm during forward flexion and backward extension in upright standing of eight asymptomatic males are measured using an inertial tracking device. The effect of variations in the lumbopelvic ratio during trunk flexion on spinal loads is quantified using a detailed musculoskeletal model. FINDINGS The mean of peak voluntary flexion rotations of the thorax, pelvis, and lumbar was 121° (SD 9.9), 53.0° (SD 5.2), and 60.2° (SD 8.6), respectively. The mean lumbopelvic ratios decreased from 2.51 in 0-30° of trunk flexion to 1.34 in 90-120° range during forward bending while it increased from 1.23 in 90-120° range to 2.86 in 0-30° range during backward extension. Variations in the lumbopelvic ratio from 0.5 to 3 (with an interval of 0.25) at any trunk flexion angle generally reduced the L5-S1 compression and shear forces by up to 21 and 45%, respectively. The measured lumbopelvic ratios resulted overall in near-optimal (minimal) L5-S1 compression forces. INTERPRETATION A simultaneous rhythm between the lumbar and pelvis movements was found during both forward and backward trunk movements. While the lumbar spine contributed more to the trunk rotation during early and final stages of forward flexion and backward extension, respectively, the pelvis contributed more during final and early stages of forward flexion and backward extension, respectively. Our healthy subjects adapted a lumbopelvic coordination that diminished L5-S1 compression force.

Trunk biomechanical models based on equilibrium at a single-level violate equilibrium at other levels

Accurate estimation of muscle forces in various occupational tasks is critical for a reliable evaluation of spinal loads and subsequent assessment of risk of injury and management of back disorders. The majority of biomechanical models of multi-segmental spine estimate muscle forces and spinal loads based on the balance of net moments at a single level with no consideration for the equilibrium at remaining levels. This work aimed to quantify the extent of equilibrium violation and alterations in estimations when such models are performed at different levels. Results are compared with those of kinematics-driven model that satisfies equilibrium at all levels and EMG data. Regardless of the method used (optimization or EMG-assisted), single-level free body diagram models yielded estimations that substantially altered depending on the level considered (i.e., level dependency). Equilibrium of net moment was also grossly violated at remaining levels with the error increasing in more demanding tasks. These models may, however, be used to estimate spinal compression forces.

Relative efficiency of abdominal muscles in spine stability

Using an iterative kinematics-driven nonlinear finite element model, relative efficiency of individual abdominal muscles in spinal stability in upright standing posture was investigated. Effect of load height on stability and muscle activities was also computed under different coactivity levels in abdominal muscles. The internal oblique was the most efficient muscle (compared with the external oblique and rectus abdominus) in providing stability while generating smaller spinal loads with lower fatigue rate of muscles. As the weight was held higher, stability deteriorated requiring additional flexor–extensor activities. The stabilising efficacy of abdominal muscles diminished at higher activities. The difference in critical loads in frontal and sagittal planes computed in the absence of abdominal coactivity disappeared under prescribed coactivities suggesting an optimal system in stability. The central nervous system may settle for a less stable spine in favour of lowering the risk of injury. Findings could help introduce stability criterion in optimisation models.

Predictive equations for lumbar spine loads in load-dependent asymmetric one- and two-handed lifting activities

BACKGROUND Asymmetric lifting activities are associated with low back pain. METHODS A finite element biomechanical model is used to estimate spinal loads during one- and two-handed asymmetric static lifting activities. Model input variables are thorax flexion angle, load magnitude as well as load sagittal and lateral positions while response variables are L4-L5 and L5-S1 disc compression and shear forces. A number of levels are considered for each input variable and all their possible combinations are introduced into the model. Robust yet user-friendly predictive equations that relate model responses to its inputs are established. FINDINGS Predictive equations with adequate goodness-of-fit (R(2) ranged from ~94% to 99%, P≤0.001) that relate spinal loads to task (input) variables are established. Contour plots are used to identify combinations of task variable levels that yield spine loads beyond the recommended limits. The effect of uncertainties in the measurements of asymmetry-related inputs on spinal loads is studied. INTERPRETATION A number of issues regarding the NIOSH asymmetry multiplier are discussed and it is concluded that this multiplier should depend on the trunk posture and be defined in terms of the load vertical and horizontal positions. Due to an imprecise adjustment of the handled load magnitude this multiplier inadequately controls the biomechanical loading of the spine. Ergonomists and bioengineers, faced with the dilemma of using either complex but more accurate models on one hand or less accurate but simple models on the other hand, have hereby easy-to-use predictive equations that quantify spinal loads under various occupational tasks.

Design optimization of an above-knee prosthesis based on the kinematics of gait

A dynamic model of an above-knee prosthesis during the complete gait cycle was developed. The model was based on a two-dimensional multi-body mechanical system and included a hydraulic and an elastic controller for the knee and a kinematical driver controller for the prosthetic ankle. The equations of motion were driven using Lagrange method. Simulation of the foot contact was conducted using a two-point penetration contact model. The knee elastic and hydraulic controller units, the knee extension stop, and the kinematical driver controller of the ankle were represented by a spring and a dashpot, a nonlinear spring, and a torsional spring-damper within a standard prosthetic configuration. The hip trajectory and net joint moment were considered as the initial conditions of the coupled differential equations. Design optimization of the prosthesis, to achieve the closest knee flexion pattern to that of the normal gait, resulted in a good correlation; the average differences with normal data were 3.3 and 3.4 deg for prosthetic knee and ankle joints, respectively. A parametric study showed that both increase and decrease of the stiffness by 50% caused an earlier knee flexion in stance phase and a lower knee flexion in swing phase. The effect of hydraulic controller damping coefficient on the flexion pattern of the prosthetic knee and ankle was only significant in the swing phase of the gait cycle.

Trunk biomechanics during maximum isometric axial torque exertions in upright standing

BACKGROUND Activities involving axial trunk rotations/moments are common and are considered as risk factors for low back disorders. Previous biomechanical models have failed to accurately estimate the trunk maximal axial torque exertion. Moreover, the trunk stability under maximal torque exertions has not been investigated. METHODS A nonlinear thoracolumbar finite element model along with the Kinematics-driven approach is used to study biomechanics of maximal axial torque generation during upright standing posture. Detailed anatomy of trunk muscles with six distinct fascicles for each abdominal oblique muscle on each side is considered. While simulating an in vivo study of maximal axial torque exertion, effects of antagonistic coactivities, coupled moments and maximum muscle stress on results are investigated. FINDINGS Predictions for trunk axial torque strength and relative muscle activities compared well with reported measurements. Trunk strength in axial torque was only slightly influenced by variations in coupled moments. Presence of abdominal antagonistic coactivities and alterations in maximum strength of muscles had, however, greater effect on maximal torque exertion. Abdominal oblique muscles play crucial role in generating moments in all three planes while back muscles are mainly effective in balancing moments in sagittal/coronal planes. Trunk stability is not of a concern in maximum axial torque exertions nor is it improved by antagonistic abdominal coactivities. INTERPRETATION In contrast to previous biomechanical model studies, the Kinematics-driven approach accurately predicts the trunk response in maximal isometric axial torque exertions by taking into account detailed anatomy of abdominal oblique muscles while satisfying equilibrium requirements in all planes/directions. In maximal torque exertions, the spine is at much higher risk of tissue injury due to large segmental loads than of instability.

A novel approach to evaluate abdominal coactivities for optimal spinal stability and compression force in lifting

A novel optimisation algorithm is developed to predict coactivity of abdominal muscles while accounting for both trunk stability via the lowest buckling load (P cr) and tissue loading via the axial compression (F c). A nonlinear multi-joint kinematics-driven model of the spine along with the response surface methodology are used to establish empirical expressions for P cr and F c as functions of abdominal muscle coactivities and external load magnitude during lifting in upright standing posture. A two-component objective function involving F c and P cr is defined. Due to opposite demands, abdominal coactivities that simultaneously maximise P cr and minimise F c cannot exist. Optimal solutions are thus identified while striking a compromise between requirements on trunk stability and risk of injury. The oblique muscles are found most efficient as compared with the rectus abdominus. Results indicate that higher abdominal coactivities should be avoided during heavier lifting tasks as they reduce stability margin while increasing spinal loads.

Relative performances of artificial neural network and regression mapping tools in evaluation of spinal loads and muscle forces during static lifting

Two artificial neural networks (ANNs) are constructed, trained, and tested to map inputs of a complex trunk finite element (FE) model to its outputs for spinal loads and muscle forces. Five input variables (thorax flexion angle, load magnitude, its anterior and lateral positions, load handling technique, i.e., one- or two-handed static lifting) and four model outputs (L4-L5 and L5-S1 disc compression and anterior-posterior shear forces) for spinal loads and 76 model outputs (forces in individual trunk muscles) are considered. Moreover, full quadratic regression equations mapping input-outputs of the model developed here for muscle forces and previously for spine loads are used to compare the relative accuracy of these two mapping tools (ANN and regression equations). Results indicate that the ANNs are more accurate in mapping input-output relationships of the FE model (RMSE= 20.7 N for spinal loads and RMSE= 4.7 N for muscle forces) as compared to regression equations (RMSE= 120.4 N for spinal loads and RMSE=43.2 N for muscle forces). Quadratic regression equations map up to second order variations of outputs with inputs while ANNs capture higher order variations too. Despite satisfactory achievement in estimating overall muscle forces by the ANN, some inadequacies are noted including assigning force to antagonistic muscles with no activity in the optimization algorithm of the FE model or predicting slightly different forces in bilateral pair muscles in symmetric lifting activities. Using these user-friendly tools spine loads and trunk muscle forces during symmetric and asymmetric static lifts can be easily estimated.

Transient analysis of trunk response in sudden release loading using kinematics-driven finite element model

BACKGROUND Sudden trunk perturbations occur in various occupational and sport activities. Despite numerous measurement studies, no comprehensive modeling simulations have yet been attempted to investigate trunk biodynamics under sudden loading/unloading. METHODS Dynamic kinematics-driven approach was used to evaluate the temporal variation of trunk muscle forces, internal loads and stability before and after a sudden release of a posterior horizontal load. Measured post-disturbance trunk kinematics, as input, and muscle electromyography (EMG) activities, for qualitative validation, were considered. FINDINGS Computed agonist and antagonist muscle forces before and after release agreed well with reported EMG activities and demonstrated basic response characteristics such as activation latency and reflex activation. The trunk was found quite stable before release and in early post-release period. Larger applied load substantially increased trunk kinematics, muscle forces and spinal loads. INTERPRETATION Excessive spinal loads due to large muscle forces in sudden loading conditions is a risk factor as the central nervous system attempts to reflexively control the sudden disturbances, a situation that further deteriorates under larger perturbations and longer latency periods. Predictions indicate the potential of the kinematics-driven model in ergonomics as well as training and rehabilitation programs.