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

How older adults regulate lateral stepping on narrowing walking paths

Walking humans often navigate complex, varying walking paths. To reduce falls, we must first determine how older adults purposefully vary their steps in contexts that challenge balance. Here, 20 young (21.7±2.6 yrs) and 18 older (71.6±6.0 yrs) healthy adults walked on virtual paths that slowly narrowed (from 45 cm to as narrow as 5 cm). Participants could switch onto an "easier" path whenever they chose. We applied our Goal Equivalent Manifold framework to quantify how participants adjusted their lateral stepping variability and step-to-step corrections of step width and lateral position as these paths narrowed. We also extracted these characteristics at the locations where participants switched paths. As paths narrowed, all participants reduced their lateral stepping variability, but older adults less so. To stay on the narrowing paths, young adults increasingly corrected step-to-step deviations in lateral position more, by correcting step-to-step deviations in step width less. Conversely, as older adults also increasingly corrected lateral position deviations, they did so without sacrificing correcting step-to-step deviations in step width, presumably to preserve balance. While older adults left the narrowing paths sooner, several of their lateral stepping characteristics remained similar to those of younger adults. Older adults largely maintained overall walking performance per se, but they did so by changing how they balanced the competing stepping regulation requirements intrinsic to the task: maintaining position vs. step width. Thus, balancing how to achieve multiple concurrent stepping goals while walking provides older adults the flexibility they need to appropriately adapt their stepping on continuously narrowing walking paths.

Does joint impedance improve dynamic leg simulations with explicit and implicit solvers?

The nervous system predicts and executes complex motion of body segments actuated by the coordinated action of muscles. When a stroke or other traumatic injury disrupts neural processing, the impeded behavior has not only kinematic but also kinetic attributes that require interpretation. Biomechanical models could allow medical specialists to observe these dynamic variables and instantaneously diagnose mobility issues that may otherwise remain unnoticed. However, the real-time and subject-specific dynamic computations necessitate the optimization these simulations. In this study, we explored the effects of intrinsic viscoelasticity, choice of numerical integration method, and decrease in sampling frequency on the accuracy and stability of the simulation. The bipedal model with 17 rotational degrees of freedom (DOF)-describing hip, knee, ankle, and standing foot contact-was instrumented with viscoelastic elements with a resting length in the middle of the DOF range of motion. The accumulation of numerical errors was evaluated in dynamic simulations using swing-phase experimental kinematics. The relationship between viscoelasticity, sampling rates, and the integrator type was evaluated. The optimal selection of these three factors resulted in an accurate reconstruction of joint kinematics (err < 1%) and kinetics (err < 5%) with increased simulation time steps. Notably, joint viscoelasticity reduced the integration errors of explicit methods and had minimal to no additional benefit for implicit methods. Gained insights have the potential to improve diagnostic tools and accurize real-time feedback simulations used in the functional recovery of neuromuscular diseases and intuitive control of modern prosthetic solutions.

A simple model of human walking

Aim. We investigate Alexander’s inverted pendulum model, the simplest mathematical model of human walking. Although it successfully explains some kinematic features of human walking, such as the velocity of the body's centre of mass, it does not account for others, like the vertical reaction force and the maximum walking speed. This paper aims to minimally extend Alexander’s model in such a way as to make it a viable and quantitative model of human walking for clinical biomechanics.Material and methods. In order to compare the predictions of Alexander’s model with experimental data on walking, we incorporate in it a robust phenomenological relation between stride frequency and stride length derived in the literature, and we introduce a step-angle dependent muscle force along the pendulum. We then analytically solve the pendulum's motion equation and find the corresponding analytical expression for the average walking speed.Results. The values of the average walking speed for different heights predicted by our model are in excellent agreement with the ones obtained in treadmill experiments. Moreover, it successfully predicts the observed walking-running transition speed, which occurs when the stride length equals the height of an individual. Finally, our extended model satisfactorily reproduces the experimentally observed ground reaction forces in the midstance and terminal stance phases. Consequently, the predicted value of the (height-dependent) maximum walking speed is in reasonable agreement with the one obtained in more sophisticated models of human walking.Conclusions. Augmented with our minimal extensions, Alexander’s model becomes an effective and realistic model of human walking applicable in clinical investigations of the human gate.

Does joint impedance improve dynamic leg simulations with explicit and implicit solvers?

The nervous system predicts and executes complex motion of body segments actuated by the coordinated action of muscles. When a stroke or other traumatic injury disrupts neural processing, the impeded behavior has not only kinematic but also kinetic attributes that require interpretation. Biomechanical models could allow medical specialists to observe these dynamic variables and instantaneously diagnose mobility issues that may otherwise remain unnoticed. However, the real-time and subject-specific dynamic computations necessitate the optimization these simulations. In this study, we explored the effects of intrinsic viscoelasticity, choice of numerical integration method, and decrease in sampling frequency on the accuracy and stability of the simulation. The bipedal model with 17 rotational degrees of freedom (DOF)-describing hip, knee, ankle, and standing foot contact-was instrumented with viscoelastic elements with a resting length in the middle of the DOF range of motion. The accumulation of numerical errors was evaluated in dynamic simulations using swing-phase experimental kinematics. The relationship between viscoelasticity, sampling rates, and the integrator type was evaluated. The optimal selection of these three factors resulted in an accurate reconstruction of joint kinematics (err < 1%) and kinetics (err < 5%) with increased simulation time steps. Notably, joint viscoelasticity reduced the integration errors of explicit methods and had minimal to no additional benefit for implicit methods . Gained insights have the potential to improve diagnostic tools and accurize real-time feedback simulations used in the functional recovery of neuromuscular diseases and intuitive control of modern prosthetic solutions.

Predicting fall risk using multiple mechanics-based metrics for a planar biped model

For both humans and robots, falls are undesirable, motivating the development of fall prediction models. Many mechanics-based fall risk metrics have been proposed and validated to varying degrees, including the extrapolated center of mass, the foot rotation index, Lyapunov exponents, joint and spatiotemporal variability, and mean spatiotemporal parameters. To obtain a best-case estimate of how well these metrics can predict fall risk both individually and in combination, this work used a planar six-link hip-knee-ankle biped model with curved feet walking at speeds ranging from 0.8 m/s to 1.2 m/s. The true number of steps to fall was determined using the mean first passage times from a Markov chain describing the gaits. In addition, each metric was estimated using the Markov chain of the gait. Because calculating the fall risk metrics from the Markov chain had not been done before, the results were validated using brute force simulations. Except for the short-term Lyapunov exponents, the Markov chains could accurately calculate the metrics. Using the Markov chain data, quadratic fall prediction models were created and evaluated. The models were further evaluated using differing length brute force simulations. None of the 49 tested fall risk metrics could accurately predict the number of steps to fall by themselves. However, when all the fall risk metrics except the Lyapunov exponents were combined into a single model, the accuracy increased substantially. These results suggest that multiple fall risk metrics must be combined to obtain a useful measure of stability. As expected, as the number of steps used to calculate the fall risk metrics increased, the accuracy and precision increased. This led to a corresponding increase in the accuracy and precision of the combined fall risk model. 300 step simulations seemed to provide the best tradeoff between accuracy and using as few steps as possible.

Barefoot walking is more stable in the gait of balance recovery in older adults

BACKGROUND

Perturbation-based balance training on a treadmill is an emerging method of gait stability training with a characteristic task nature that has had positive and sustained effects on balance recovery strategies and fall reduction. Little is known about the effects produced by shod and barefoot walking. We aimed to investigate which is more appropriate, shod or barefoot walking, for perturbation-based balance training in older adults.

METHODS

Fourteen healthy older adults (age: 68.29 ± 3.41 years; body height: 1.76 ± 0.10 m; body mass: 81.14 ± 14.52 kg) performed normal and trip-like perturbed walking trials, shod and barefoot, on a treadmill of the Gait Real-time Analysis Interactive Lab. The marker trajectories data were processed by Human Body Model software embedded in the Gait Offline Analysis Tool. The outcomes of stride length variability, stride time variability, step width variability, and swing time variability were computed and statistically analyzed by a two-way repeated-measures analysis of variance (ANOVA) based on gait pattern (normal gait versus perturbed recovery gait) and footwear condition (shod versus barefoot).

RESULTS

Footwear condition effect (p = 0.0310) and gait pattern by footwear condition interaction effect (p = 0.0055) were only observed in swing time variability. Gait pattern effects were detected in all four outcomes of gait variability.

CONCLUSIONS

Swing time variability, independent of gait speed, could be a valid indicator to differentiate between footwear conditions. The lower swing time variability in perturbed recovery gait suggests that barefoot walking may be superior to shod walking for perturbation-based balance training in older adults.

Quantifying the effect of sagittal plane joint angle variability on bipedal fall risk

Falls are a major issue for bipeds. For elderly adults, falls can have a negative impact on their quality of life and lead to increased medical costs. Fortunately, interventional methods are effective at reducing falls assuming they are prescribed. For biped robots, falls prevent them from completing required tasks. Thus, it is important to understand what aspects of gait increase fall risk. Gait variability may be associated with increased fall risk; however, previous studies have not investigated the variation in the movement of the legs. The purpose of this study was to determine the effect of joint angle variability on falling to determine which component(s) of variability were statistically significant. In order to investigate joint angle variability, a physics-based simulation model that captured joint angle variability as a function of time through Fourier series was used. This allowed the magnitude, the frequency mean, and the frequency standard deviation of the variability to be altered. For the values tested, results indicated that the magnitude of the variability had the most significant impact on falling, and specifically that the stance knee flexion variability magnitude was the most significant factor. This suggests that increasing the joint variability magnitude may increase fall risk, particularly if the controller is not able to actively compensate. Altering the variability frequency had little to no effect on falling.

Wearable Technology for Evaluation of Risk of Falls

One's risk of fall can be quantified in terms of variability in one's gait, reflecting a loss of automatic rhythm of one's gait. In gait analysis, variability is commonly understood in terms of the fluctuation in the kinematic, kinetic, spatio-temporal, or physiological information. Here, we have focused on the estimation of knee joint angle (kinematic variable) synchronized with some of the kinetic and spatio-temporal gait parameters while an individual walked overground. Our system consisted of a pair of shoes with instrumented insoles and knee flexion/extension recorder unit having bend sensors. In addition, we have used the Coefficient of Variation for estimating the variability in the knee flexion/extension angle while walking overground as an indicator of the risk of fall. A study with healthy individuals (young and old) walking overground on pathways having 0⁰ and 180⁰ turning angles indicated the feasibility of our wearable system to compute the variability in knee flexion/extension angle as an indicator of the risk of fall.

Effect of simulated sensorimotor noise on kinematic variability and stability of a biped walking model

Whether higher variability in older adults' walking is an indication of increased instability has been challenged recently. We performed a computer simulation to investigate the effect of sensorimotor noise on the kinematic variability and stability in a biped walking model. Stochastic differential equations of the system with additive Gaussian white noise was constructed and solved. Sensorimotor noise mainly resulted in higher kinematic variability but its influence on gait stability is minimal. This implies that kinematic variability evident in walking gaits of older adults could be the result of internal sensorimotor noise and not an indication of instability.

Differentiating fallers from nonfallers using nonlinear variability analyses of data from a low-cost portable footswitch device: a feasibility study

PURPOSE

Falls are one of the main causes of injuries in older adults. This study evaluated a low-cost footswitch device that was designed to measure gait variability and investigates whether there are any relationships between variability metrics and clinical balance tests for individuals with a history of previous falls.

METHODS

Sixteen older adults completed a history of falls questionnaire, three functional tests related to fall risk, and walked on a treadmill with the footswitch device. We extracted the stride times from the device and applied two nonlinear variability analyses: coefficient of variation and detrended fluctuation analysis.

RESULTS

The temporal variables and variability metrics from the footswitch device correlated with gold-standard measurements based on ground reaction force data. One variability metric (detrended fluctuation analysis) showed a significant relationship with the presence of past falls with a sensitivity of 43%.

CONCLUSION

This feasibility study demonstrates the basis for using low-cost footswitch devices to predict fall risk.

Randomness in appendage coordination facilitates strenuous ground self-righting

Randomness is common in biological and artificial systems, resulting either from stochasticity of the environment or noise in organisms or devices themselves. In locomotor control, randomness is typically considered a nuisance. For example, during dynamic walking, randomness in stochastic terrain leads to metastable dynamics, which must be mitigated to stabilize the system around limit cycles. Here, we studied whether randomness in motion is beneficial for strenuous locomotor tasks. Our study used robotic simulation modeling of strenuous, leg-assisted, winged ground self-righting observed in cockroaches, in which unusually large randomness in wing and leg motions is present. We developed a simplified simulation robot capable of generating similar self-righting behavior and varied the randomness level in wing-leg coordination. During each wing opening attempt, the more randomness added to the time delay between wing opening and leg swinging, the more likely it was for the naive robot (which did not know what coordination is best) to self-right within a finite time. Wing-leg coordination, measured by the phase between wing and leg oscillations, had a crucial impact on self-righting outcome. Without randomness, periodic wing and leg oscillations often limited the system to visit a few bad phases, leading to failure to escape from the metastable state. With randomness, the system explored phases thoroughly and had a better chance of encountering good phases to self-right. Our study complements previous work by demonstrating that randomness helps destabilize locomotor systems from being trapped in undesired metastable states, a situation common in strenuous locomotion.

Step width variability as a discriminator of age-related gait changes

BACKGROUND

There is scientific evidence that older adults aged 65 and over walk with increased step width variability which has been associated with risk of falling. However, there are presently no threshold levels that define the optimal reference range of step width variability. Thus, the purpose of our study was to estimate the optimal reference range for identifying older adults with normative and excessive step width variability.

METHODS

We searched systematically the BMC, Cochrane Library, EBSCO, Frontiers, IEEE, PubMed, Scopus, SpringerLink, Web of Science, Wiley, and PROQUEST databases until September 2018, and included the studies that measured step width variability in both younger and older adults during walking at self-selected speed. Data were pooled in meta-analysis, and standardized mean differences (SMD) with 95% confidence intervals (CI) were calculated. A single-decision threshold method based on the Youden index, and a two-decision threshold method based on the uncertain interval method were used to identify the optimal threshold levels (PROSPERO registration: CRD42018107079).

RESULTS

Ten studies were retrieved (older adults = 304; younger adults = 219). Step width variability was higher in older than in younger adults (SMD = 1.15, 95% CI = 0.60; 1.70; t = 4.72, p = 0.001). The single-decision method set the threshold level for excessive step width variability at 2.14 cm. For the two-decision method, step width variability values above the upper threshold level of 2.50 cm were considered excessive, while step width variability values below the lower threshold level of 1.97 cm were considered within the optimal reference range.

CONCLUSION

Step width variability is higher in older adults than in younger adults, with step width variability values above the upper threshold level of 2.50 cm to be considered as excessive. This information could potentially impact rehabilitation technology design for devices targeting lateral stability during walking.

How healthy older adults regulate lateral foot placement while walking in laterally destabilizing environments

Gait variability is generally associated with falls, but specific connections remain disputed. To reduce falls, we must first understand how older adults maintain lateral balance while walking, particularly when their stability is challenged. We recently developed computational models of lateral stepping, based on Goal Equivalent Manifolds, that separate effects of step-to-step regulation from variability. These show walking humans seek to strongly maintain step width, but also lateral position on their path. Here, 17 healthy older (ages 60+) and 17 healthy young (ages 18-31) adults walked in a virtual environment with no perturbations and with laterally destabilizing perturbations of either the visual field or treadmill platform. For step-to-step time series of step widths and lateral positions, we computed variability, statistical persistence and how much participants directly corrected deviations at each step. All participants exhibited significantly increased variability, decreased persistence and tighter direct control when perturbed. Simulations from our stepping regulation models indicate people responded to the increased variability imposed by these perturbations by either maintaining or tightening control of both step width and lateral position. Thus, while people strive to maintain lateral balance, they also actively strive to stay on their path. Healthy older participants exhibited slightly increased variability, but no differences from young in stepping regulation and no evidence of greater reliance on visual feedback, even when subjected to substantially destabilizing perturbations. Thus, age alone need not degrade lateral stepping control. This may help explain why directly connecting gait variability to fall risk has proven difficult.

Phase resetting and intermittent control at the edge of stability in a simple biped model generates 1/f-like gait cycle variability

The 1/f-like gait cycle variability, characterized by temporal changes in stride-time intervals during steady-state human walking, is a well-documented gait characteristic. Such gait fractality is apparent in healthy young adults, but tends to disappear in the elderly and patients with neurological diseases. However, mechanisms that give rise to gait fractality have yet to be fully clarified. We aimed to provide novel insights into neuro-mechanical mechanisms of gait fractality, based on a numerical simulation model of biped walking. A previously developed heel-toe footed, seven-rigid-link biped model with human-like body parameters in the sagittal plane was implemented and expanded. It has been shown that the gait model, stabilized rigidly by means of impedance control with large values of proportional (P) and derivative (D) gains for a linear feedback controller, is destabilized only in a low-dimensional eigenspace, as P and D decrease below and even far below critical values. Such low-dimensional linear instability can be compensated by impulsive, phase-dependent actions of nonlinear controllers (phase resetting and intermittent controllers), leading to the flexible walking with joint impedance in the model being as small as that in humans. Here, we added white noise to the model to examine P-value-dependent stochastic dynamics of the model for small D-values. The simulation results demonstrated that introduction of the nonlinear controllers in the model determined the fractal features of gait for a wide range of the P-values, provided that the model operates near the edge of stability. In other words, neither the model stabilized only by pure impedance control even at the edge of linear stability, nor the model stabilized by specific nonlinear controllers, but with P-values far inside the stability region, could induce gait fractality. Although only limited types of controllers were examined, we suggest that the impulsive nonlinear controllers and criticality could be major mechanisms for the genesis of gait fractality.

Correlations of pelvis state to foot placement do not imply within-step active control

Experimental studies of human walking have shown that within an individual step, variations in the center of mass (CoM) state can predict corresponding variations in the next foot placement. This has been interpreted by some to indicate the existence of active control in which the nervous system uses the CoM state at or near mid-stance to regulate subsequent foot placement. However, the passive dynamics of the moving body and/or moving limbs also contribute (perhaps strongly) to foot placement, and thus to its variation. The extent to which correlations of CoM state to foot placement reflect the effects of within-step active control, those of passive dynamics, or some combination of both, remains an important and still open question. Here, we used an open-loop-stable 2D walking model to show that this predictive ability cannot by itself be taken as evidence of within-step active control. In our simulations, we too find high correlations between the CoM state and subsequent foot placement, but these correlations are entirely due to passive dynamics as our system has no active control, either within a step or between steps. This demonstrates that any inferences made from such correlations about within-step active control require additional supporting evidence beyond the correlations themselves. Thus, these within-step predictive correlations leave unresolved the relative importance of within-step active control as compared to passive dynamics, meaning that such methods should be used to characterize control in human walking only with caution.

A Review on Fall Prediction and Prevention System for Personal Devices: Evaluation and Experimental Results

Injuries due to unintentional falls cause high social cost in which several systems have been developed to reduce them. Recently, two trends can be recognized. Firstly, the market is dominated by fall detection systems, which activate an alarm after a fall occurrence, but the focus is moving towards predicting and preventing a fall, as it is the most promising approach to avoid a fall injury. Secondly, personal devices, such as smartphones, are being exploited for implementing fall systems, because they are commonly carried by the user most of the day. This paper reviews various fall prediction and prevention systems, with a particular interest to the ones that can rely on the sensors embedded in a smartphone, i.e., accelerometer and gyroscope. Kinematic features obtained from the data collected from accelerometer and gyroscope have been evaluated in combination with different machine learning algorithms. An experimental analysis compares the evaluated approaches by evaluating their accuracy and ability to predict and prevent a fall. Results show that tilt features in combination with a decision tree algorithm present the best performance.

Fear of Falling Contributing to Cautious Gait Pattern in Women Exposed to a Fictional Disturbing Factor: A Non-randomized Clinical Trial

Objective: This study aimed to investigate the gait pattern of elderly women with and without fall-history, with high and low fear of falling, when exposed to a disturbing factor. Materials and Methods: Forty-nine elderly women without cognitive impairment agreed to participate. Participants were divided into four groups, considering the history of falls and fear of falling. Three-dimensional gait analysis was performed to assess gait kinematics before and after exposure to the fictional disturbing factor (psychological and non-motor agent). Results: After being exposed to the perturbation, all showed shorter step length, stride length and slower walking speed. Those without fall-history and with high fear of falling showed greater changes and lower Gait Profile Score. Conclusion: The gait changes shown in the presence of a fear-of-falling causing agent led to a cautious gait pattern in an attempt to increase protection. However, those changes increased fall-risk, boosted by fear of falling. Clinical Trial Registration: www.residentialclinics.gov.br, identifier: RBR-35xhj5.

Is there sufficient evidence to explain the cause of sexually dimorphic behaviour in force steadiness?

Neuromuscular noise is a determining factor in the control of isometric force steadiness (FS), quantified as coefficient of variation (CV) of force around a preestablished target output. In this paper we examine sex-related differences of neural, muscular, and tendon influences on neuromuscular noise to understand FS in females and males. We use evidence from the literature to identify that CV of force is higher in females compared with males in the upper and lower body, with sex-related differences becoming less apparent with increasing age. Evaluation of sex-related physiology in tandem with results from FS studies indicate that differences in fibre type, contractile properties, and number of motor units (MUs) are unlikely contributors to differences in FS between females and males. MU type, behaviour of the population (inclusive of number of active MUs from the population), agonist–antagonist activity, maximal strength, and tendon mechanics are probable contributors to sexually dimorphic behaviour in FS. To clearly determine underlying causes of sex-related differences in FS, further study and reporting between females and males is required. Females and males are included in many studies; however, rich data on sexually dimorphic behaviour is lost when data are collapsed across sex or identified as nonsignificant without supporting values. This poses a challenge to identifying the underlying cause of females having higher CV of force than males. This review provides evidence of sexually dimorphic behaviour in FS and suggests that physiological differences between females and males effect neuromuscular noise, and in-turn contribute to sex-related differences in FS.

Local dynamic stability during treadmill walking can detect children with developmental coordination disorder

OBJECTIVE

Developmental coordination disorder (DCD) is an innate impairment of motor coordination that affects basic locomotion and balance. This study investigated local dynamic stability of trunk accelerations during treadmill walking as an objective evaluation of gait stability and the sensitivity and specificity of this measure to discriminate children with DCD from typically developing children.

METHOD

Eight children with DCD and ten age- and gender-matched typically developing children (TD) walked four minutes on a treadmill. Trunk accelerations in vertical, medio-lateral and anterior-posterior directions were recorded with a sternum mounted accelerometer at 256Hz. Short term local dynamic stability (λs), root mean square (RMS) and relative root mean square (RMSR) were calculated from measures of orthogonal trunk accelerations. Receiver operating characteristic curve (ROC) analysis was performed to discriminate between groups based on short term local dynamic stability.

RESULTS

λs was significantly greater in children with DCD in the main movement direction (AP) (DCD: 1.69±0.17 λs; TD:1.41±0.17 λs; p=0.005), indicating reduced local dynamic stability. RMS and RMSR accelerations showed no difference between children with DCD and TD children in any direction. The ROC analysis of λs in separate directions and in two dimensions showed an excellent accuracy of discriminating between children with DCD and TD children. Anterior-posterior direction in combination with medio-lateral or vertical showed best performance with an area under the curve (AUC) of 0.91.

CONCLUSION

We have shown that children with developmental coordination disorder have general reduced local dynamic stability and that the short term Lyapunov exponent has good power of discrimination between DCD and TD.

Does dynamic stability govern propulsive force generation in human walking?

Before succumbing to slower speeds, older adults may walk with a diminished push-off to prioritize stability over mobility. However, direct evidence for trade-offs between push-off intensity and balance control in human walking, independent of changes in speed, has remained elusive. As a critical first step, we conducted two experiments to investigate: (i) the independent effects of walking speed and propulsive force (F_P) generation on dynamic stability in young adults, and (ii) the extent to which young adults prioritize dynamic stability in selecting their preferred combination of walking speed and F_P generation. Subjects walked on a force-measuring treadmill across a range of speeds as well as at constant speeds while modulating their F_P according to a visual biofeedback paradigm based on real-time force measurements. In contrast to improvements when walking slower, walking with a diminished push-off worsened dynamic stability by up to 32%. Rather, we find that young adults adopt an F_P at their preferred walking speed that maximizes dynamic stability. One implication of these findings is that the onset of a diminished push-off in old age may independently contribute to poorer balance control and precipitate slower walking speeds.

Increased gait variability may not imply impaired stride-to-stride control of walking in healthy older adults: Winner: 2013 Gait and Clinical Movement Analysis Society Best Paper Award

Older adults exhibit increased gait variability that is associated with fall history and predicts future falls. It is not known to what extent this increased variability results from increased physiological noise versus a decreased ability to regulate walking movements. To "walk", a person must move a finite distance in finite time, making stride length (L_n) and time (T_n) the fundamental stride variables to define forward walking. Multiple age-related physiological changes increase neuromotor noise, increasing gait variability. If older adults also alter how they regulate their stride variables, this could further exacerbate that variability. We previously developed a Goal Equivalent Manifold (GEM) computational framework specifically to separate these causes of variability. Here, we apply this framework to identify how both young and high-functioning healthy older adults regulate stepping from each stride to the next. Healthy older adults exhibited increased gait variability, independent of walking speed. However, despite this, these healthy older adults also concurrently exhibited no differences (all p>0.50) from young adults either in how their stride variability was distributed relative to the GEM or in how they regulated, from stride to stride, either their basic stepping variables or deviations relative to the GEM. Using a validated computational model, we found these experimental findings were consistent with increased gait variability arising solely from increased neuromotor noise, and not from changes in stride-to-stride control. Thus, age-related increased gait variability likely precedes impaired stepping control. This suggests these changes may in turn precede increased fall risk.

Incorporating Human-like Walking Variability in an HZD-Based Bipedal Model

Predictive simulations of human walking could be used to investigate a wide range of questions. Promising moderately complex models have been developed using the robotics control technique hybrid zero dynamics (HZD). Existing simulations of human walking only consider the mean motion, so they cannot be used to investigate fall risk, which is correlated with variability. This work determines how to incorporate human-like variability into an HZD-based healthy human model to generate a more realistic gait. The key challenge is determining how to combine the existing mathematical description of variability with the dynamic model so that the biped is still able to walk without falling. To do so, the commanded motion is augmented with a sinusoidal variability function and a polynomial correction function. The variability function captures the variation in joint angles while the correction function prevents the variability function from growing uncontrollably. The necessity of the correction function and the improvements with a reduction of stance ankle variability are demonstrated via simulations. The variability in temporal measures is shown to be similar to experimental values.

Formation mechanism of a basin of attraction for passive dynamic walking induced by intrinsic hyperbolicity

Passive dynamic walking is a useful model for investigating the mechanical functions of the body that produce energy-efficient walking. The basin of attraction is very small and thin, and it has a fractal-like shape; this explains the difficulty in producing stable passive dynamic walking. The underlying mechanism that produces these geometric characteristics was not known. In this paper, we consider this from the viewpoint of dynamical systems theory, and we use the simplest walking model to clarify the mechanism that forms the basin of attraction for passive dynamic walking. We show that the intrinsic saddle-type hyperbolicity of the upright equilibrium point in the governing dynamics plays an important role in the geometrical characteristics of the basin of attraction; this contributes to our understanding of the stability mechanism of bipedal walking.

Stride-Time Variability and Fall Risk in Persons with Multiple Sclerosis

Gait variability is associated with falls in clinical populations. However, gait variability's link to falls in persons with Multiple Sclerosis (PwMS) is not well established. This investigation examined the relationship between stride-time variability, fall risk, and physiological fall risk factors in PwMS. 17 PwMS (62.8 ± 7.4 years) and 17 age-matched controls (62.8 ± 5.9 years) performed the 6-minute walk test. Stride-time was assessed with accelerometers attached to the participants' shanks. Stride-time variability was measured by interstride coefficient of variation (CV) of stride-time. The participant's fall risk was measured by the short form physiological profile assessment (PPA). A Spearman correlation analysis was used to determine the relationship between variables. Increased fall risk was strongly associated with increased stride-time CV in both PwMS (ρ = 0.71, p < 0.01) and the controls (ρ = 0.67, p < 0.01). Fall risk was not correlated with average stride-time (p > 0.05). In PwMS, stride-time CV was related to postural sway (ρ = 0.74, p < 0.01) while in the control group, it was related to proprioception (ρ = 0.61, p < 0.01) and postural sway (ρ = 0.78, p < 0.01). Current observations suggest that gait variability is maybe more sensitive marker of fall risk than average gait parameters in PwMS. It was also noted that postural sway may be potentially targeted to modify gait variability in PwMS.

Does long-distance walking improve or deteriorate walking stability of transtibial amputees?

BACKGROUND

Falls are common in transtibial amputees which are linked to their poor stability. While amputees are encouraged to walk more, they are more vulnerable to fatigue which leads to even poorer walking stability. The objective of this study was to evaluate the dynamic stability of amputees after long-distance walking.

METHODS

Six male unilateral transtibial amputees (age: 53 (SD: 8.8); height: 170cm (SD: 3.4); weight: 75kg (SD: 4.7)) performed two sessions (30minutes each) of treadmill walking, separated by a short period of gait tests. Gait tests were performed before the walking (baseline) and after each session of treadmill walking. Gait parameters and their variability across repeated steps at each of the three conditions were computed.

FINDINGS

There were no significant differences in walking speed, step length, stance time, time of occurrence, and magnitude of peak angular velocities of the knee and hip joint (P>0.05). However, variability of knee and hip angular velocity after 30-minute walking was significantly higher than the baseline (P<0.05) and after a total of 60-minute walking (P<0.05). The variability of lateral sway velocity after 30-minute walking was significantly higher than the baseline (P<0.05).

INTERPRETATION

The significant increase in variability after 30-minute walking could indicate poorer walking stability when fatigue was developed, while the significant reduction after 60-minute walking might indicate the ability of amputees to restore their walking stability after further continuous walking.

Examination of spatiotemporal gait parameters during the 6-min walk in individuals with multiple sclerosis

This investigation examined spatiotemporal parameters of gait during the 6-min walk (6MW) in individuals with multiple sclerosis (MS) and in healthy controls. Eighteen individuals with MS [divided into those who were independently ambulatory (n=10) and those who were ambulatory with assistance (n=8)] and 10 healthy controls performed a 6MW while recording spatiotemporal gait parameters using a pressure-sensitive walkway. Parameters recorded were walking velocity, cadence, step length and width, step time, percent of the gait cycle in double support, and variability of step length and width, step time, and double support. The ambulatory with assistance MS group had a significantly greater reduction in walking velocity (P=0.000) over the course of the 6MW, which coincided with a significantly greater increase in step time and double support (P=0.029) than in the other groups. Only the ambulatory with assistance MS group showed an increase in step-time variability and double-support variability during the 6MW (P's<0.05). The novel results indicate that the reduction in velocity over prolonged walking occurs through a greater change in the temporal parameters of gait in persons with MS who require assistance while walking. In addition, the increase in gait variability in the individuals with MS who require assistance while walking indicates that the control over walking further deteriorates over the course of the 6MW.

Role of visual input in the control of dynamic balance: variability and instability of gait in treadmill walking while blindfolded

While vision obviously plays an essential role in orienting and obstacle avoidance, its role in the regulation of dynamic balance is not yet fully understood. The objective of this study was to assess dynamic stability while blindfolded, under optimal conditions that minimized the fear of falling. The hypothesis was that visual deprivation could be compensated for by using other sensory strategies to stabilize gait. One hundred healthy adults (aged 20-69 years) participated in the study. They were previously accustomed to blindfolded treadmill walking wearing a safety harness. Their preferred walking speeds (PWS) were assessed with eyes open (PWSEO) and with eyes closed (blindfolded, PWSEC). Three five-minute tests were performed: (A) normal walking at PWSEO, (B) blindfolded walking at PWSEC, and (C) normal walking at PWSEC. Trunk acceleration was measured with a lightweight inertial sensor. Dynamic stability was assessed by using (1) acceleration root mean square (RMS), which estimates the variability of the signal, and hence, the smoothness of the trunk movement and (2) local dynamic stability (LDS), which reflects the efficiency of the motor control to stabilize the trunk. Although walking at PWSEC with eyes open (comparing conditions A and C) had a slight impact on gait stability (relative difference: RMS +4 %, LDS -5 %), no destabilizing effect of visual deprivation (B vs. C, RMS -4 %, LDS -1 %) was observed. Therefore, it is concluded that when reassuring conditions are offered to individuals while walking, they are able to adopt alternative sensory strategies to control dynamic equilibrium without the help of vision.

To What Extent Does Not Wearing Shoes Affect the Local Dynamic Stability of Walking?: Effect Size and Intrasession Repeatability

Local dynamic stability (stability) quantifies how a system responds to small perturbations. Several experimental and clinical findings have highlighted the association between gait stability and fall risk. Walking without shoes is known to slightly modify gait parameters. Barefoot walking may cause unusual sensory feedback to individuals accustomed to shod walking, and this may affect stability. The objective was therefore to compare the stability of shod and barefoot walking in healthy individuals and to analyze the intrasession repeatability. Forty participants traversed a 70 m indoor corridor wearing normal shoes in one trial and walking barefoot in a second trial. Trunk accelerations were recorded with a 3D-accelerometer attached to the lower back. The stability was computed using the finite-time maximal Lyapunov exponent method. Absolute agreement between the forward and backward paths was estimated with the intraclass correlation coefficient (ICC). Barefoot walking did not significantly modify the stability as compared with shod walking (average standardized effect size: +0.11). The intrasession repeatability was high (ICC: 0.73–0.81) and slightly higher in barefoot walking condition (ICC: 0.81–0.87). Therefore, it seems that barefoot walking can be used to evaluate stability without introducing a bias as compared with shod walking, and with a sufficient reliability.

Differential effects of fatigue on movement variability

When individuals perform purposeful actions to fatigue, there is typically a general decline in their movement performance. This study was designed to investigate the effects exercise-induced fatigue has on lower limb kinetics and kinematics during a side-step cutting task. In particular, it was of interest to determine what changes could be seen in mean amplitude and all metrics of signal variability with fatigue. The results of the study revealed that post-fatigue there was an overall decrease in absolute force production as reflected by a decline in mean amplitude and variability (SD) of the ground reaction forces (GRFV and GRFML). A decrease in mean and SD of the knee moments were also observed post-exercise. Interestingly, this trend was not mirrored by similar changes in time-dependent properties of these signals. Instead, there was an increase in the SampEn values (reflecting a more variable, irregular signal) for GRF force profiles, knee kinematics and moments following the exercise-induced fatigue. These results illustrate that fatigue can have differential effects on movement variability, resulting in a both an increase and decrease in movement variability, depending on the variable selected. Thus, the impact of fatigue is not simply restricted to a decline in force producing capacity of the system but more importantly it demonstrates that the ability of the person to perform a smooth and controlled action is limited due to fatigue.

Using dynamic walking models to identify factors that contribute to increased risk of falling in older adults

Falls are common in older adults. The most common cause of falls is tripping while walking. Simulation studies demonstrated that older adults may be restricted by lower limb strength and movement speed to regain balance after a trip. This review examines how modeling approaches can be used to determine how different measures predict actual fall risk and what some of the causal mechanisms of fall risk are. Although increased gait variability predicts increased fall risk experimentally, it is not clear which variability measures could best be used, or what magnitude of change corresponded with increased fall risk. With a simulation study we showed that the increase in fall risk with a certain increase in gait variability was greatly influenced by the initial level of variability. Gait variability can therefore not easily be used to predict fall risk. We therefore explored other measures that may be related to fall risk and investigated the relationship between stability measures such as Floquet multipliers and local divergence exponents and actual fall risk in a dynamic walking model. We demonstrated that short-term local divergence exponents were a good early predictor for fall risk. Neuronal noise increases with age. It has however not been fully understood if increased neuronal noise would cause an increased fall risk. With our dynamic walking model we showed that increased neuronal noise caused increased fall risk. Although people who are at increased risk of falling reduce their walking speed it had been questioned whether this slower speed would actually cause a reduced fall risk. With our model we demonstrated that a reduced walking speed caused a reduction in fall risk. This may be due to the decreased kinematic variability as a result of the reduced signal-dependent noise of the smaller muscle forces that are required for slower. These insights may be used in the development of fall prevention programs in order to better identify those at increased risk of falling and to target those factors that influence fall risk most.

Non-linear dynamics of human locomotion: effects of rhythmic auditory cueing on local dynamic stability

It has been observed that times series of gait parameters [stride length (SL), stride time (ST), and stride speed (SS)], exhibit long-term persistence and fractal-like properties. Synchronizing steps with rhythmic auditory stimuli modifies the persistent fluctuation pattern to anti-persistence. Another non-linear method estimates the degree of resilience of gait control to small perturbations, i.e., the local dynamic stability (LDS). The method makes use of the maximal Lyapunov exponent, which estimates how fast a non-linear system embedded in a reconstructed state space (attractor) diverges after an infinitesimal perturbation. We propose to use an instrumented treadmill to simultaneously measure basic gait parameters (time series of SL, ST, and SS from which the statistical persistence among consecutive strides can be assessed), and the trajectory of the center of pressure (from which the LDS can be estimated). In 20 healthy participants, the response to rhythmic auditory cueing (RAC) of LDS and of statistical persistence [assessed with detrended fluctuation analysis (DFA)] was compared. By analyzing the divergence curves, we observed that long-term LDS (computed as the reverse of the average logarithmic rate of divergence between the 4th and the 10th strides downstream from nearest neighbors in the reconstructed attractor) was strongly enhanced (relative change +73%). That is likely the indication of a more dampened dynamics. The change in short-term LDS (divergence over one step) was smaller (+3%). DFA results (scaling exponents) confirmed an anti-persistent pattern in ST, SL, and SS. Long-term LDS (but not short-term LDS) and scaling exponents exhibited a significant correlation between them (r = 0.7). Both phenomena probably result from the more conscious/voluntary gait control that is required by RAC. We suggest that LDS and statistical persistence should be used to evaluate the efficiency of cueing therapy in patients with neurological gait disorders.

Local dynamic stability as a responsive index for the evaluation of rehabilitation effect on fall risk in patients with multiple sclerosis: a longitudinal study

BACKGROUND

Gait and balance problems are common in patients with multiple sclerosis, leading to high risk for falls. Local Dynamic Stability (LDS), a non-linear gait stability index, has been advocated as an early indicator of risk for falls. With this longitudinal study over three weeks, we aimed to assess the responsiveness of Local Dynamic Stability to a rehabilitation program and to compare it to other measures.

METHODS

Eighteen patients (mean 54 years, median EDSS score: 5) participated. They were admitted to inpatient rehabilitation and received a three weeks individually tailored program. They performed a 3-minute walking test at the beginning and at the end of the stay, as well as pain, wellbeing, fatigue, and balance assessment. The Local Dynamic Stability was computed from the acceleration signals measured with a 3D-accelerometer.

RESULTS

At the end of the rehabilitation process, patients reported reduced pain (Effect Size: -0.7), fatigue (ES:-0.6), and increased wellbeing (ES: 1.1). A small positive effect on static balance was observed (ES: 0.3). LDS was improved (ES: 0.6), and the effect was higher than walking speed improvement (ES: 0.4).

CONCLUSIONS

The Local Dynamic Stability seemed responsive to assess rehabilitation effects in patients with multiple sclerosis. It could constitute a valuable gait quality index, which could evaluate potential effects of rehabilitation on fall risk.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN69803702.

Influence of neuromuscular noise and walking speed on fall risk and dynamic stability in a 3D dynamic walking model

Older adults and those with increased fall risk tend to walk slower. They may do this voluntarily to reduce their fall risk. However, both slower and faster walking speeds can predict increased risk of different types of falls. The mechanisms that contribute to fall risk across speeds are not well known. Faster walking requires greater forward propulsion, generated by larger muscle forces. However, greater muscle activation induces increased signal-dependent neuromuscular noise. These speed-related increases in neuromuscular noise may contribute to the increased fall risk observed at faster walking speeds. Using a 3D dynamic walking model, we systematically varied walking speed without and with physiologically-appropriate neuromuscular noise. We quantified how actual fall risk changed with gait speed, how neuromuscular noise affected speed-related changes in fall risk, and how well orbital and local dynamic stability measures predicted changes in fall risk across speeds. When we included physiologically-appropriate noise to the 'push-off' force in our model, fall risk increased with increasing walking speed. Changes in kinematic variability, orbital, and local dynamic stability did not predict these speed-related changes in fall risk. Thus, the increased neuromuscular variability that results from increased signal-dependent noise that is necessitated by the greater muscular force requirements of faster walking may contribute to the increased fall risk observed at faster walking speeds. The lower fall risk observed at slower speeds supports experimental evidence that slowing down can be an effective strategy to reduce fall risk. This may help explain the slower walking speeds observed in older adults and others.

Gait variability and disability in multiple sclerosis

Gait variability is clinically relevant in some populations, but there is limited documentation of gait variability in persons with multiple sclerosis (MS). This investigation examined average and variability of spatiotemporal gait parameters in persons with MS and healthy controls and subsequent associations with disability status. 88 individuals with MS (age 52.4±11.1) and 20 healthy controls (age 50.9±8.7) performed two self-paced walking trials on a 7.9-m electronic walkway to determine gait parameters. Disability was indexed by the Expanded Disability Status Scale (EDSS) and ranged between 2.5 and 6.5. Gait variability was indexed by standard deviation (SD) and coefficient of variation (CV=SD/mean) of step time, step length, and step width. Average gait parameters were significantly correlated with EDSS (ρ=0.756-0.609) and were significantly different in individuals with MS compared to controls (p≤0.002). Also, step length (p<0.001) and step time (p<0.001) variability were both significantly greater in MS compared to controls. EDSS was positively correlated with step length variability and individuals with MS who used assistive devices to walk had significantly greater step length variability than those who walked independently (p's<.05). EDSS was correlated with step time and length variability even when age was taken into account. Additionally, Fisher's z test of partial correlations revealed that average gait parameters were more closely related to disability status than gait variability in individuals with MS. This suggests that focusing on average gait parameters may be more important than variability in therapeutic interventions in MS.

Variability in inter-joint coordination during walking of elderly adults and its association with clinical balance measures

BACKGROUND

Walking requires coordination among multiple joints. Little is known about the association between the coordination ability and fall risks in elderly adults. This study investigated variability of inter-joint coordination in elderly adults and determined its correlation to clinical balance measures.

METHODS

Gait analyses of 15 non-fallers and 15 fallers were performed during walking. Continuous relative phase, derived from phase angles of two adjacent joints, was used to assess the inter-joint coordination. Variability of inter-joint coordination was calculated as the average standard deviation of all points on the ensemble continuous relative phase curve over a gait cycle, namely the deviation phase. Outcomes from three clinical balance tests, including Berg Balance Test, Dynamic Gait Index and Timed Up-and-Go, were examined.

FINDINGS

No significant group differences were detected in hip-knee deviation phase values after accounting for differences in walking speeds. For the knee-ankle deviation phase, fallers demonstrated significantly greater values in the stance phase but smaller values in the swing phase. The hip-knee deviation phase values demonstrated a negative correlation with Dynamic Gait Index, and the knee-ankle deviation phase values had a negative correlation with Dynamic Gait Index and a positive correlation with Timed Up-and-Go time.

INTERPRETATION

Excessive variability of the supporting limb and reduced variability of the swing limb in knee-ankle inter-joint coordination of fallers may contribute to their risk of imbalance or tripping during walking. Compared to Berg Balance Test and Timed Up-and-Go, Dynamic Gait Index scores might be more sensitive to reflect declines in inter-joint coordination during walking.

Assessing the stability of human locomotion: a review of current measures

Falling poses a major threat to the steadily growing population of the elderly in modern-day society. A major challenge in the prevention of falls is the identification of individuals who are at risk of falling owing to an unstable gait. At present, several methods are available for estimating gait stability, each with its own advantages and disadvantages. In this paper, we review the currently available measures: the maximum Lyapunov exponent (λS and λL), the maximum Floquet multiplier, variability measures, long-range correlations, extrapolated centre of mass, stabilizing and destabilizing forces, foot placement estimator, gait sensitivity norm and maximum allowable perturbation. We explain what these measures represent and how they are calculated, and we assess their validity, divided up into construct validity, predictive validity in simple models, convergent validity in experimental studies, and predictive validity in observational studies. We conclude that (i) the validity of variability measures and λS is best supported across all levels, (ii) the maximum Floquet multiplier and λL have good construct validity, but negative predictive validity in models, negative convergent validity and (for λL) negative predictive validity in observational studies, (iii) long-range correlations lack construct validity and predictive validity in models and have negative convergent validity, and (iv) measures derived from perturbation experiments have good construct validity, but data are lacking on convergent validity in experimental studies and predictive validity in observational studies. In closing, directions for future research on dynamic gait stability are discussed.

Do orthopaedic shoes improve local dynamic stability of gait? An observational study in patients with chronic foot and ankle injuries

Background

Complex foot and ankle fractures, such as calcaneum fractures or Lisfranc dislocations, are often associated with a poor outcome, especially in terms of gait capacity. Indeed, degenerative changes often lead to chronic pain and chronic functional limitations. Prescription footwear represents an important therapeutic tool during the rehabilitation process. Local Dynamic Stability (LDS) is the ability of locomotor system to maintain continuous walking by accommodating small perturbations that occur naturally during walking. Because it reflects the degree of control over the gait, LDS has been advocated as a relevant indicator for evaluating different conditions and pathologies. The aim of this study was to analyze changes in LDS induced by orthopaedic shoes in patients with persistent foot and ankle injuries. We hypothesised that footwear adaptation might help patients to improve gait control, which could lead to higher LDS:

Methods

Twenty-five middle-aged inpatients (5 females, 20 males) participated in the study. They were treated for chronic post-traumatic disabilities following ankle and/or foot fractures in a Swiss rehabilitation clinic. During their stay, included inpatients received orthopaedic shoes with custom-made orthoses (insoles). They performed two 30s walking trials with standard shoes and two 30s trials with orthopaedic shoes. A triaxial motion sensor recorded 3D accelerations at the lower back level. LDS was assessed by computing divergence exponents in the acceleration signals (maximal Lyapunov exponents). Pain was evaluated with Visual Analogue Scale (VAS). LDS and pain differences between the trials with standard shoes and the trials with orthopaedic shoes were assessed.

Results

Orthopaedic shoes significantly improved LDS in the three axes (medio-lateral: 10% relative change, paired t-test p < 0.001; vertical: 9%, p = 0.03; antero-posterior: 7%, p = 0.04). A significant decrease in pain level (VAS score -29%) was observed.

Conclusions

Footwear adaptation led to pain relief and to improved foot & ankle proprioception. It is likely that that enhancement allows patients to better control foot placement. As a result, higher dynamic stability has been observed. LDS seems therefore a valuable index that could be used in early evaluation of footwear outcome in clinical settings.

Gait variability and multiple sclerosis

Gait variability, that is, fluctuations in movement during walking, is an indicator of walking function and has been associated with various adverse outcomes such as falls. In this paper, current research concerning gait variability in persons with multiple sclerosis (MS) is discussed. It is well established that persons with MS have greater gait variability compared to age and gender matched controls without MS. The reasons for the increase in gait variability are not completely understood. Evidence indicates that disability level, assistive device use, attentional requirement, and fatigue are related to gait variability in persons with MS. Future research should address the time-evolving structure (i.e., temporal characteristics) of gait variability, the clinical importance of gait variability, and underlying mechanisms that drive gait variability in individuals with MS.

Footfall placement variability and falls in multiple sclerosis

Gait variability (i.e., fluctuations in walking) provides unique information about the control of movement and is associated with falls. This investigation examined the association between gait variability and falls in persons with multiple sclerosis (MS) and healthy controls. Traditional distributional metrics of gait variability (i.e., coefficient of variation (CV)) and a novel metric based on Fourier series analysis of footfall placement variability were determined for 41 individuals with MS and 20 age- and sex-matched controls. Spatiotemporal parameters of gait were collected using a 7.9 m electronic walkway that recorded individual footfalls during steady state comfortable walking. Persons with MS were divided into two groups based on fall history (non-fallers and recurrent fallers). Overall, persons with MS had greater gait variability than controls as indexed by CV and Fourier-based variability (p's < 0.05). Moreover, recurrent fallers with MS had greater Fourier-based variability than non-fallers with MS (p = 0.025), whereas there was no difference in MS groups in traditional gait variability metrics (p > 0.05). These observations highlight that footfall placement variability is related to fall status in MS. Future work determining the sensitivity of footfall placement variability to dysfunction is warranted.

Local dynamic stability and variability of gait are associated with fall history in elderly subjects

Gait parameters that can be measured with simple instrumentation may hold promise for identifying individuals at risk of falling. Increased variability of gait is associated with increased risk of falling, but research on additional parameters indicates that local dynamic stability (LDS) of gait may also be a predictor of fall risk. The objective of the present study was to assess the association between gait variability, LDS of gait and fall history in a large sample of elderly subjects. Subjects were recruited and tested at a large national fair. One hundred and thirty four elderly, aged 50-75, who were able to walk without aids on a treadmill, agreed to participate. After subjects walked on a treadmill, LDS (higher values indicate more instability) and variability parameters were calculated from accelerometer signals (trunk worn). Fall history was obtained by self-report of falls in the past 12 months. Gait variability and short-term LDS were, individually and combined, positively associated with fall history. In conclusion, both increased gait variability and increased short-term LDS are possible risk factors for falling in the elderly.

Are spontaneous fractures possible? An example of clinical application for personalised, multiscale neuro-musculo-skeletal modelling

Elderly frequently present variable degrees of osteopenia, sarcopenia, and neuromotor control degradation. Severely osteoporotic patients sometime fracture their femoral neck when falling. Is it possible that such fractures might occur without any fall, but rather spontaneously while the patient is performing normal movements such as level walking? The aim of this study was to verify if such spontaneous fractures are biomechanically possible, and in such case, which conditions of osteoporosis, sarcopenia, and neuromotor degradation could produce them. To the purpose, a probabilistic multiscale body-organ model validated against controlled experiments was used to predict the risk of spontaneous fractures in a population of 80-years old women, with normal weight and musculoskeletal anatomy, and variable degree of osteopenia, sarcopenia, and neuromotor control degradation. A multi-body inverse dynamics sub-model, coupled to a probabilistic neuromuscular sub-model, and to a femur finite element sub-model, formed the multiscale model, which was run within a Monte Carlo stochastic scheme, where the various parameters were varied randomly according to well defined distributions. The model predicted that neither extreme osteoporosis, nor extreme neuromotor degradation alone are sufficient to predict spontaneous fractures. However, when the two factors are combined an incidence of 0.4% of spontaneous fractures is predicted for the simulated population, which is consistent with clinical reports. When the model represented only severely osteoporotic patients, the incidence of spontaneous fractures increased to 29%. Thus, is biomechanically possible that spontaneous femoral neck fractures occur during level walking, due to a combination of severe osteoporosis and severe neuromotor degradation.

Influence of simulated neuromuscular noise on the dynamic stability and fall risk of a 3D dynamic walking model

Measures that can predict risk of falling are essential for enrollment of older adults into fall prevention programs. Local and orbital stability directly quantify responses to very small perturbations and are therefore putative candidates for predicting fall risk. However, research to date is not conclusive on whether and how these measures relate to fall risk. Testing this empirically would be time consuming or may require high risk tripping experiments. Simulation studies therefore provide an important tool to initially explore potential measures to predict fall risk. This study performed simulations with a 3D dynamic walking model to explore if and how dynamic stability measures predict fall risk. The model incorporated a lateral step controller to maintain lateral stability. Neuronal noise of increasing amplitude was added to this controller to manipulate fall risk. Short-term (λ(S)(*)) local instability did predict fall risk, but long-term (λ(L)(*)) local instability and orbital stability (maxFM) did not. Additionally, λ(S)(*) was an early predictor for fall risk as it started increasing before fall risk increased. Therefore, λ(S)(*) could be a very useful tool to identify older adults whose fall risk is about to increase, so they can be enrolled in fall prevention programs before they actually fall.