Disturbance type and gait speed affect fall direction and impact location

Since falling to the side and impacting on or near the hip increase hip fracture risk, we examined the fall direction and pelvis impact location resulting from four disturbances (faint, slip, step down, trip) at three gait speeds (fast, normal, slow) in 14 young adults instructed not to attempt recovery. We hypothesized that certain disturbances such as faints and slips and slow walking speed were more likely to result in an impact on the hip. For each trial, the fall direction, impact location and pelvis impact velocity were measured. The results showed that both disturbance type and gait speed significantly affected fall direction and impact location (analysis of covariance with repeated measures, p< or =0.0001) with a significant interaction (p<0.05). Trips and steps down usually resulted in forward falls, with frontal impacts regardless of gait speed. At fast gait speed, slips and faints also usually resulted in forward falls, with frontal impacts. As gait speed decreased, however, slips usually resulted in sideways or backward falls, with impact on the hip or buttocks, and faints resulted in a greater number of sideways falls, with impact near the hip. Therefore, compared to other disturbances and gait speeds, slipping or fainting while walking slowly was more likely to result in an impact on the hip, suggesting a greater risk for hip fracture. Furthermore, 56% of the impact velocities generated were within one standard deviation of the estimate of the mean impact velocity needed to fracture an elderly femur.     

Wrist impact velocities are smaller in forward falls than backward falls from standing

The wrist is a common fracture site for both young and older adults. The purpose of this study was to compare wrist kinematics in backward and forward falls with different fall protective responses. We carried out within-subject comparison of impact velocities and maximum velocities during descent of the distal radius among three different fall configurations: (a) backward falls with knees flexed, (b) backward falls with knees extended and (c) forward falls with knees flexed. We also examined the effect of fall configuration on fall durations, elbow flexion, trunk flexion and forearm angles at impact. Forward falls resulted in smaller impact velocities of the distal radius, longer fall duration, longer braking duration, greater elbow flexion and more horizontal landing position of the forearm compared to backward falls. The distal radius impact velocity during forward falls (1.33 m/s) was significantly lower than in backward falls, and among the backward falls the impact velocity of the flexed knee strategy (2.01 m/s) was significantly lower than the extended knee strategy (2.27 m/s). These impact velocities were significantly reduced from the maximum velocities observed during descent (forward falls=3.57 m/s, backward falls with knee flexed=3.16 m/s, backward falls with knees extended=3.52 m/s). We conclude that (1) smaller impact velocities of the wrists in forward falls could imply a lower fracture risk compared to backward falls, and (2) fall protective responses reduced wrist impact velocities in all fall directions.     

Reliability of impact forces, hip angles and velocities during simulated forward falls using a novel Propelled Upper Limb fall ARrest Impact System (PULARIS)

Previous forward fall simulation methods have provided good kinematic and kinetic data, but are limited in that they have started the falls from a stationary position and have primarily simulated uni-directional motion. Therefore, a novel Propelled Upper Limb fall ARest Impact System (PULARIS) was designed to address these issues during assessments of a variety of fall scenarios. The purpose of this study was to present PULARIS and evaluate its ability to impact the upper extremities of participants with repeatable velocities, hand forces and hip angles in postures and with vertical and horizontal motion consistent with forward fall arrest. PULARIS consists of four steel tubing crossbars in a scissor-like arrangement that ride on metal trolleys within c-channel tracks in the ceiling. Participants are suspended beneath PULARIS by the legs and torso in a prone position and propelled horizontally via a motor and chain drive until they are quick released, and then impact floor-mounted force platforms with both hands. PULARIS velocity, hip angles and velocities and impact hand forces of ten participants (five male, five female) were collected during three fall types (straight-arm, self-selected and bent-arm) and two fall heights (0.05 m and 0.10 m) to assess the reliability of the impact conditions provided by the system. PULARIS and participant hip velocities were found to be quite repeatable (mean ICC?=?0.81) with small between trial errors (mean?=?0.03 m/s). The ratio of horizontal to vertical hip velocity components (~0.75) agreed well with previously reported data (0.70-0.80). Peak vertical hand impact forces were also found to be relatively consistent between trials with a mean ICC of 0.73 and mean between trial error of 13.4 N. Up to 83% of the horizontal hand impact forces displayed good to excellent reliability (ICC?>?0.6) with small between trial differences. Finally, the ICCs for between trial hip angles were all classified as good to excellent. Overall, PULARIS is a reliable method and is appropriate for studying the response of the distal upper extremity to impact loading during non-stationary, multi-directional movements indicative of a forward fall. This system performed well at different fall heights, and allows for a variety of upper and lower extremity, and hip postures to be tested successfully in different landing scenarios consistent with elderly and sport-related falls.     

Responses to gait perturbations in stroke survivors who prospectively experienced falls or no falls

Background: Steady-state gait characteristics appear promising as predictors of falls in stroke survivors. However, assessing how stroke survivors respond to actual gait perturbations may result in better fall predictions. We hypothesize that stroke survivors who fall have a diminished ability to adequately adjust gait characteristics after gait is perturbed. This study explored whether gait characteristics of perturbed gait differ between fallers and non fallers. Method: Chronic stroke survivors were recruited by clinical therapy practices. Prospective falls were monitored over a six months follow up period. We used the Gait Real-time Analysis Interactive Lab (GRAIL, Motekforce Link B.V., Amsterdam) to assess gait. First we assessed gait characteristics during steady-state gait and second we examined gait responses after six types of gait perturbations. We assessed base of support gait characteristics and margins of stability in the forward and medio-lateral direction. Findings: Thirty eight stroke survivors complete our gait protocol. Fifteen stroke survivors experienced falls. All six gait perturbations resulted in a significant gait deviation. Forward stability was reduced in the fall group during the second step after a ipsilateral perturbation. Interpretation: Although stability was different between groups during a ipsilateral perturbation, it was caused by a secondary strategy to keep up with the belt speed, therefore, contrary to our hypothesis fallers group of stroke survivors have a preserved ability to cope with external gait perturbations as compared to non fallers. Yet, our sample size was limited and thereby, perhaps minor group differences were not revealed in the present study.     

Are Subject-Specific Musculoskeletal Models Robust to the Uncertainties in Parameter Identification?

Subject-specific musculoskeletal modeling can be applied to study musculoskeletal disorders, allowing inclusion of personalized anatomy and properties. Independent of the tools used for model creation, there are unavoidable uncertainties associated with parameter identification, whose effect on model predictions is still not fully understood. The aim of the present study was to analyze the sensitivity of subject-specific model predictions (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the uncertainties in the identification of body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. The uncertainties in input variables had a moderate effect on model predictions, as muscle and joint contact forces showed maximum standard deviation of 0.3 times body-weight and maximum range of 2.1 times body-weight. In addition, the output variables significantly correlated with few input variables (up to 7 out of 312) across the gait cycle, including the geometry definition of larger muscles and the maximum muscle tension in limited gait portions. Although we found subject-specific models not markedly sensitive to parameter identification, researchers should be aware of the model precision in relation to the intended application. In fact, force predictions could be affected by an uncertainty in the same order of magnitude of its value, although this condition has low probability to occur.     

Slip-induced fall-risk assessment based on regular gait pattern in older adults

Aging-associated fall-risk assessment is crucial for fall prevention. Thus, this study aimed to develop a prognostic model to predict fall-risk following an unexpected over-ground slip perturbation based on normal gait pattern in healthy older adults. 112 healthy older adults who experienced a novel slip in a safe laboratory environment were included. Their slip trial and natural walking trial immediately prior to it were analyzed. To identify the best fall-risk predictive model, gait related variables including step length, segment angles, center of mass state, and ground reaction force (GRF) were determined and inputted into a stepwise logistic regression. The optimal slip-induced fall prediction model was based on the right thigh angle at slipping foot touchdown (TD), the maximum GRF of the slipping limb after TD, and the momentum change from TD to recovery foot liftoff (LO), with an overall prediction accuracy of 75.9%, predicting 74.5% of falls (sensitivity) and 77.2% of recoveries (specificity). Conversely, a model based on clinical and demographic measures predicted 78.2% of falls and 47.4% of recoveries, resulting in a much lower overall accuracy of 62.5%. The fall-risk model based on normal gait pattern which was developed for slip-induced perturbations in healthy older adults was able to provide a high predictive accuracy. This information could provide insight about the ideal normal gait measures which could be used to contribute towards development of therapeutic strategies related to dynamic balance and fall prevention to enhance preventive interventions in populations with high-risk for slip-induced falls.     

Identification of passive elastic joint moment-angle relationships in the lower extremity

The purpose of this study was to develop a method for identifying subject-specific passive elastic joint moment-angle relationships in the lower extremity, which could subsequently be used to estimate passive contributions to joint kinetics during gait. Twenty healthy young adults participated in the study. Subjects were positioned side-lying with their dominant limb supported on a table via low-friction carts. A physical therapist slowly manipulated the limb through full sagittal hip, knee, and ankle ranges of motion using two hand-held 3D load cells. Lower extremity kinematics, measured with a passive marker motion capture system, and load cell readings were used to compute joint angles and associated passive joint moments. We formulated a passive joint moment-angle model that included eight exponential functions to account for forces generated via the passive stretch of uni-articular structures and bi-articular muscles. Model parameters were estimated for individual subjects by minimizing the sum of squared errors between model predicted and experimentally measured moments. The model predictions closely replicated measured joint moments with average root-mean-squared errors of 2.5, 1.4, and 0.7 Nm about the hip, knee, and ankle respectively. We show that the models can be coupled with gait kinematics to estimate passive joint moments during walking. Passive hip moments were substantial from terminal stance through initial swing, with energy being stored as the hip extended and subsequently returned during pre- and initial swing. We conclude that the proposed methodology could provide quantitative insights into the potentially important role that passive mechanisms play in both normal and abnormal gait.     

The relation between hip impact velocity and hip impact force differs between sideways fall techniques.

Fall techniques that reduce fall severity may decrease the risk of hip fractures. A fundamental variable for fall severity is impact force, but impact velocity is also used. The purpose of the study was to determine whether impact velocity is valid to determine differences in fall severity between different techniques. Five young adults with martial arts (MA) experience performed sideways falls from kneeling height using three techniques: Block with arm (Block) and MA techniques with and without use of the arm to break the fall. In addition, one subject also performed MA falls from standing height. Linear regression analysis showed a moderate relation between hip impact velocity and force, which was depended on technique. In falls with comparable impact velocities, forces in MA falls were lower than forces in Block falls. Hence, differences in impact force could not be predicted by velocity. In conclusion, hip impact velocity may be useful to make an approximate prediction of impact force within fall techniques. However, to determine differences between techniques it was not always a valid predictor. When direct impact force measurements are not possible, methods combining impact velocity with energy estimates before and after impact might be more valid.     

Martial arts fall techniques reduce hip impact forces in naive subjects after a brief period of training.

Hip fractures are among the most serious consequences of falls in the elderly. Martial arts (MA) fall techniques may reduce hip fracture risk, as they are known to reduce hip impact forces by approximately 30% in experienced fallers. The purpose of this study was to investigate whether hip impact forces and velocities in MA falls would be smaller than in a 'natural' fall arrest strategy (Block) in young adults (without any prior experience) after a 30-min training session in sideways MA fall techniques. Ten subjects fell sideways from kneeling height. In order to identify experience-related differences, additional EMG data of both fall types were collected in inexperienced (n=10) and experienced fallers (n=5). Compared to Block falls, MA falls had significantly smaller hip impact forces (-17%) and velocities (-7%). EMG results revealed experience-related differences in the execution of the MA fall, indicative of less pronounced trunk rotation in the inexperienced fallers. This may explain their smaller reduction of impact forces compared to experienced fallers. In conclusion, the finding that a substantial reduction in impact forces can be achieved after a short training in MA techniques is very promising with respect to their use in interventions to prevent fall injuries.     

Influence of simulated neuromuscular noise on movement variability and fall risk in a 3D dynamic walking model

People at risk of falling exhibit increased gait variability, which may predict future falls. However, the causal mechanisms underlying these correlations are not well known. Increased neuronal noise associated with aging likely leads to increased gait variability, which could in turn lead to increased fall risk. This paper presents a model of how changes in neuromuscular noise independently affect gait variability and probability of falling, and aims to determine the extent to which changes in gait variability directly predict fall risk. We used a dynamic walking model that incorporates a lateral step controller to maintain lateral stability. Noise was applied to this controller to approximate neuromuscular noise in humans. Noise amplitude was varied between low amplitudes that did not induce falls and high amplitudes for which the model always fell. With increases in noise amplitude, the model fell more often and after fewer steps. Gait variability increased with noise amplitude and predicted increased probability of falling. Importantly, these relationships were not linear. At either low gait variability or very high gait variability, small increases in noise and variability affected probability of falling very little. Conversely, at intermediate noise and/or variability levels, the same small increases resulted in large increases in probability of falling. Our results validate the idea that age-related increases in neuromuscular noise likely play a direct contributing role in increasing fall risk. However, neuromuscular noise remains only one of many important factors that need to be considered. These findings have important implications for fall prevention research and practice.     

Predictive Simulation Generates Human Adaptations during Loaded and Inclined Walking

Predictive simulation is a powerful approach for analyzing human locomotion. Unlike techniques that track experimental data, predictive simulations synthesize gaits by minimizing a high-level objective such as metabolic energy expenditure while satisfying task requirements like achieving a target velocity. The fidelity of predictive gait simulations has only been systematically evaluated for locomotion data on flat ground. In this study, we construct a predictive simulation framework based on energy minimization and use it to generate normal walking, along with walking with a range of carried loads and up a range of inclines. The simulation is muscle-driven and includes controllers based on muscle force and stretch reflexes and contact state of the legs. We demonstrate how human-like locomotor strategies emerge from adapting the model to a range of environmental changes. Our simulation dynamics not only show good agreement with experimental data for normal walking on flat ground (92% of joint angle trajectories and 78% of joint torque trajectories lie within 1 standard deviation of experimental data), but also reproduce many of the salient changes in joint angles, joint moments, muscle coordination, and metabolic energy expenditure observed in experimental studies of loaded and inclined walking.     

Protective movements during sideways falls from standing height

To examine the effect of protective movements during sideways falls from standing height (i.e., from the standing position), a two-step study was performed. In the first step, 80 young male and female volunteers freely fell onto a sport-mat. All falls were recorded on videotape, and replayed to analyze movements in response to the falls. Several protective movements were observed; forward flexion and lateral flexion were observed with a particularly high frequency. In the second step, impact velocities of the head and hip were measured by a three-dimensional motion analyzer regarding three types of falls: stiff falls, forward flexion falls and lateral flexion falls. Both types of flexion reduced impact velocities of the head, but not those of the hip. The reduction of the impact velocity on the head correlated with the lowering of the height of the head from the floor.     

Effect of pre-impact movement strategies on the impact forces resulting from a lateral fall

Approximately 90% of hip fractures in older adults result from falls, mostly from landing on or near the hip. A three-dimensional, 11-segment, forward dynamic biomechanical model was developed to investigate whether segment movement strategies prior to impact can affect the impact forces resulting from a lateral fall. Four different pre-impact movement strategies, with and without using the ipsilateral arm to break the fall, were implemented using paired actuators representing the agonist and antagonist muscles acting about each joint. Proportional-derivative feedback controller controlled joint angles and velocities so as to minimize risk of fracture at any of the impact sites. It was hypothesized that (a) the use of active knee, hip and arm joint torques during the pre-contact phase affects neither the whole body kinetic energy at impact nor the peak impact forces on the knee, hip or shoulder and (b) muscle strength and reaction time do not substantially affect peak impact forces. The results demonstrate that, compared with falling laterally as a rigid body, an arrest strategy that combines flexion of the lower extremities, ground contact with the side of the lower leg along with an axial rotation to progressively present the posterolateral aspects of the thigh, pelvis and then torso, can reduce the peak hip impact force by up to 56%. A 30% decline in muscle strength did not markedly affect the effectiveness of that fall strategy. However, a 300-ms delay in implementing the movement strategy inevitably caused hip impact forces consistent with fracture unless the arm was used to break the fall prior to the hip impact.     

Evaluation of the minimum energy hypothesis and other potential optimality criteria for human running

A popular hypothesis for human running is that gait mechanics and muscular activity are optimized in order to minimize the cost of transport (CoT). Humans running at any particular speed appear to naturally select a stride length that maintains a low CoT when compared with other possible stride lengths. However, it is unknown if the nervous system prioritizes the CoT itself for minimization, or if some other quantity is minimized and a low CoT is a consequential effect. To address this question, we generated predictive computer simulations of running using an anatomically inspired musculoskeletal model and compared the results with data collected from human runners. Three simulations were generated by minimizing the CoT, the total muscle activation or the total muscle stress, respectively. While all the simulations qualitatively resembled real human running, minimizing activation predicted the most realistic joint angles and timing of muscular activity. While minimizing the CoT naturally predicted the lowest CoT, minimizing activation predicted a more realistic CoT in comparison with the experimental mean. The results suggest a potential control strategy centred on muscle activation for economical running.     

Quantitative analysis of upper limbs during gait: a marker set protocol

Purpose: to develop a marker set for simultaneously assessing upper and lower limb biomechanics during gait.Methods: 24 healthy young subjects (mean age: 23.80 years) were assessed quantitatively using an optoelectronic system, two force platform and a video system. Passive markers were positioned according to the proposed marker set which enables acquiring the upper and lower limb movement simultaneously during Gait Analysis. In addition to the traditional parameters obtained from Gait Analysis, the shoulder and elbow angles were computed from markers coordinates of upper limbs; then, some significant parameters were identified and calculated. From shoulder and elbow position, angles, angular velocities, angular acceleration, moments, and powers were calculated for shoulder and elbow joints. Results: Kinematic and kinetic data were obtained in the three planes (sagittal, frontal, and transversal) for the shoulder and in the sagittal plane for the elbow. Normative ranges were obtained for these parameters from data of healthy participants. Conclusions: The proposed experimental set-up enables simultaneous assessment of upper and lower limb movement during gait. Thus, no further trials are required in addition to those acquired during standard gait analysis in order to assess upper limb motion, which also makes the experimental set-up feasible for clinical applications.     

Computer simulation of human body dynamics

Understanding human body dynamics is important in many situations, such as automobile and aircraft crashes, aircraft ejections, falls, and other acceleration environments. The design of automobile interiors, cockpits, and safety equipment requires knowledge of the forces and accelerations encountered during an emergency. Because of the limited information available from actual events and the various constraints in testing, computer simulations are often the only means of obtaining detailed information. The Armstrong Laboratory (AL) developed the Articulated Total Body (ATB) model to predict the human body dynamics in many of these environments. This model is a three-dimensional rigid body dynamics program in which the human body is modeled as a series of segments. Forces on the body segments are calculated based on their interaction with the surroundings including seat and cockpit surfaces. The model also calculates the internal joint resistive and constraint forces. Because of this capability to predict both internal and external forces acting on the body, the ATB model can be used in investigating injuries. It is also a valuable design tool for evaluating safety of proposed systems before prototypes are built or costly tests conducted. When testing is conducted, the model provides data that cannot be measured, such as forces within the body, and supplementing test data with parameter variation simulations. To validate the model, tests such as those conducted on the AL impact sled are simulated. Test films and instrumentation data are compared with simulation graphics and quantitative output to gain confidence in the simulation results.     

Estimating severity of sideways fall using a generic multi linear regression model based on kinematic input variables

Many research groups have studied fall impact mechanics to understand how fall severity can be reduced to prevent hip fractures. Yet, direct impact force measurements with force plates are restricted to a very limited repertoire of experimental falls. The purpose of this study was to develop a generic model for estimating hip impact forces (i.e. fall severity) in in vivo sideways falls without the use of force plates.Twelve experienced judokas performed sideways Martial Arts (MA) and Block (‘natural’) falls on a force plate, both with and without a mat on top. Data were analyzed to determine the hip impact force and to derive 11 selected (subject-specific and kinematic) variables. Falls from kneeling height were used to perform a stepwise regression procedure to assess the effects of these input variables and build the model.The final model includes four input variables, involving one subject-specific measure and three kinematic variables: maximum upper body deceleration, body mass, shoulder angle at the instant of ‘maximum impact’ and maximum hip deceleration. The results showed that estimated and measured hip impact forces were linearly related (explained variances ranging from 46 to 63%). Hip impact forces of MA falls onto the mat from a standing position (3650 ± 916 N) estimated by the final model were comparable with measured values (3698 ± 689 N), even though these data were not used for training the model. In conclusion, a generic linear regression model was developed that enables the assessment of fall severity through kinematic measures of sideways falls, without using force plates.     

Comparative assessment of bone pose estimation using Point Cluster Technique and OpenSim

Estimating the position of the bones from optical motion capture data is a challenge associated with human movement analysis. Bone pose estimation techniques such as the Point Cluster Technique (PCT) and simulations of movement through software packages such as OpenSim are used to minimize soft tissue artifact and estimate skeletal position; however, using different methods for analysis may produce differing kinematic results which could lead to differences in clinical interpretation such as a misclassification of normal or pathological gait. This study evaluated the differences present in knee joint kinematics as a result of calculating joint angles using various techniques. We calculated knee joint kinematics from experimental gait data using the standard PCT, the least squares approach in OpenSim applied to experimental marker data, and the least squares approach in OpenSim applied to the results of the PCT algorithm. Maximum and resultant RMS differences in knee angles were calculated between all techniques. We observed differences in flexion/extension, varus/valgus, and internal/external rotation angles between all approaches. The largest differences were between the PCT results and all results calculated using OpenSim. The RMS differences averaged nearly 5° for flexion/extension angles with maximum differences exceeding 15°. Average RMS differences were relatively small (< 1.08°) between results calculated within OpenSim, suggesting that the choice of marker weighting is not critical to the results of the least squares inverse kinematics calculations. The largest difference between techniques appeared to be a constant offset between the PCT and all OpenSim results, which may be due to differences in the definition of anatomical reference frames, scaling of musculoskeletal models, and/or placement of virtual markers within OpenSim. Different methods for data analysis can produce largely different kinematic results, which could lead to the misclassification of normal or pathological gait. Improved techniques to allow non-uniform scaling of generic models to more accurately reflect subject-specific bone geometries and anatomical reference frames may reduce differences between bone pose estimation techniques and allow for comparison across gait analysis platforms.