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Because fall experiments with volunteers can be both challenging and risky, especially with older volunteers, we wished to develop computer simulations of falls to provide a theoretical framework for understanding and extending experimental results. To perform a preliminary validation of the articulated total body (ATB) model for passive falls, we compared the model predictions of fall direction, impact location, and impact velocity as a function of disturbance type (faint, slip, step down, trip) and gait speed (fast, normal, slow) to experimental results with young adult volunteers. The three-dimensional ATB model had 17 segments and 16 joints. Its physical characteristics, environment definitions, contact functions, and initial conditions were representative of our experiment. For each combination of disturbance and gait speed, the ATB model was left to fall passively under gravity once disturbed, i.e., no joint torques were applied, until impact with the floor occurred. Finally, we also determined the sensitivity of the model predictions to changes in the model’s parameters. Our model predictions of fall angles and impact angles were qualitatively in agreement with those observed experimentally for ten and seven of the 12 original simulations, respectively. Quantitatively, the model predictions of fall angles, impact angles, and impact velocities were within one experimental standard deviation for seven, three, and nine of the 12 original simulations, respectively, and within two experimental standard deviations for ten, nine, and 11 of the 12 original simulations, respectively. Finally, the fall angle and impact angle region did not change for 92% and 95% of the 74 input variation simulations, respectively, and the impact velocities were within the experimental standard deviations for 78% of the 74 input variation simulations. Based on our simulations and a sensitivity analysis, we conclude that our preliminary validation of the ATB model for passive falls was successful. In fact, these ATB model simulations represent a significant step forward in fall simulations. We believe that with additional work, the ATB model could be used to accurately simulate a variety of human falls and may be useful in further understanding the etiology and mechanisms of fall injuries such as hip fractures.

We measured the step response of a surrogate human pelvis/impact pendulum system at force levels between 50 and 350 N. We then fit measured response curves with four different single-degree-of-freedom models, each possessing a single mass, and supports of the following types: standard linear solid, Voigt, Maxwell, and spring. We then compared model predictions of impact force during high-energy collisions (pendulum impact velocity ranging from 1.16 to 2.58 m/s) to force traces from actual impacts to the surrogate pelvis. We found that measured peak impact forces, which ranged from 1700 to 5600 N, were best predicted by the mass-spring, Maxwell, and standard linear solid models, each of which had average errors less than 3 percent. Reduced accuracy was observed for the commonly used Voigt model, which exhibited an average error of 10 percent. Considering that the surrogate pelvis system used in this study exhibited nonlinear stiffness and damping similar to that observed in simulated fall impact experiments with human volunteers, our results suggest that these simple models allow impact forces in potentially traumatic falls to be predicted to within reasonable accuracy from the measured response of the body in safe, simulated collisions.

Despite our growing understanding of the importance of fall mechanics in the etiology of hip fracture, previous studies have largely ignored the kinematics and dynamics of falls from standing height. Beginning from basic principles, we estimated peak impact force on the greater trochanter in a sideways fall from standing height. Using a one degree-of-freedom impact model, this force is determined by the impact velocity of the hip, the effective mass of that part of the body that is moving prior to impact, and the overall stiffness of the soft tissue overlying the hip. To determine impact velocity and effective mass, three different paradigms of increasing complexity were used: 1) a falling point mass or a rigid bar pivoting at its base; 2) two-link models consisting of a leg segment and a torso; and 3) three-link models including a knee. The total mechanical energy of each model before falling was equated to the total mechanical energy just prior to impact in order to estimate the hip impact velocity. In addition, the configuration of the model just before impact was used to estimate the effective mass. Our model predictions were compared with the results of an earlier experimental study with young subjects falling on a 10-inch thick mattress. Values from literature were used to estimate the soft tissue stiffness. For the models, predicted values for hip impact velocity and effective mass ranged from 2.47 to 4.34 m/s and from 15.9 to 70.0 kg, respectively. Predicted values for the peak force applied to the greater trochanter ranged from 2.90k to 9.99k N. Based on comparisons to the experimental falls, impact velocity and impact force were best predicted by a simple two-link model with the trunk at 45 degrees to the vertical at impact. A three-link model with a quadratic spring incorporated in the knee of the model was the best predictor of effective mass. Using our most accurate model, the peak impact force was 2.90k N for a 5th percentile female and 4.26k N for a 95th percentile female, thereby confirming the widely held perception that “the bigger they are, the harder they fall.”

Over 90 percent of the more than 250,000 hip fractures that occur annually in the United States are the result of falls from standing height. Despite this, the stresses associated with femoral fracture from a fall have not been investigated previously. Our objectives were to use three-dimensional finite element models of the proximal femur (with geometries and material properties based directly on quantitative computed tomography) to compare predicted stress distributions for one-legged stance and for a fall to the lateral greater trochanter. We also wished to test the correspondence between model predictions and in vitro strain gage data and failure loads for cadaveric femora subjected to these loading conditions. An additional goal was to use the model predictions to compare the sensitivity of several imaging sites in the proximal femur which are used for the in vivo prediction of hip fracture risk. In this first of two parts, linear finite element models of two unpaired human cadaveric femora were generated. In Part II, the models were extended to include nonlinear material properties for the cortical and trabecular bone. While there was poor correspondence between strain gage data and model predictions, there was excellent agreement between the in vitro failure data and the linear model, especially using a von Mises effective strain failure criterion. Both the onset of structural yielding (within 22 and 4 percent) and the load at fracture (within 8 and 5 percent) were predicted accurately for the two femora tested. For the simulation of one-legged stance, the peak stresses occurred in the primary compressive trabeculae of the subcapital region. However, for a simulated fall, the peak stresses were in the intertrochanteric region. The Ward’s triangle (basicervical) site commonly used for the clinical assessment of osteoporosis was not heavily loaded in either situation. These findings suggest that the intertrochanteric region may be the most sensitive site for the assessment of fracture risk due to a fall and the subcapital region for fracture risk due to repetitive activities such as walking.

A three-dimensional, linear finite element model was generated for an intact plexiglass tube with an attached six-hole stainless steel compression plate. We examined external forces representing axial, off-center axial, and four-point bending, along with superimposed plate and screw pretension. Strain gage experiments were conducted to test model validity and the finite element results were contrasted to a composite beam theory solution. Excellent correspondence was observed between finite element and strain gage data for the most significant strain components. Composite beam theory tended to overestimate the neutral axis shift which results from plate application. The model also demonstrated fracture site distraction due to plate pretension, and the tendency for outer screw failure for the combination of bending-closed with a preload in the plate and screws.

Based on a regular array of cubic unit cells, each containing a body-centered spherical void, we created an idealized three-dimensional model for both subchondral trabecular bone and a class of porous foams. By considering only face-to-face stacking of unit cells, the inherent symmetry was such that, except at the surface, the displacements and stresses within any one unit cell were representative of the entire porous structure. Using prescribed displacements the model was loaded in both uniaxial compressive strain and uniaxial shear strain. Based on the response to these loads, we found the tensor of elastic constants for an equivalent homogeneous elastic solid with cubic symmetry. We then compared the predicted modulus with our experimental values for bovine trabecular bone and literature values for an open-celled latex rubber foam.

A theoretical formulation for studying limb motions and joint kinetics by multiaxial accelerometry is developed. The technique is designed to study the swing phase of human gait, modeling the lower leg as a rigid body. Major advantages of the approach are that acceleration information needed for the calculation of forces and moments is generated directly, and that the method automatically generates its own initial conditions. Results of validation experiments using both artificial and experimental data demonstrate that the method is theoretically valid, but that it taxes available instrumentation and requires further development before it can be applied in a clinical setting.