Walking Cadence Affects the Recruitment of the Medial-Lateral Balance Mechanisms

Assessment of stabilizing feedback control of walking: A tutorial

Walking without falling requires stabilization of the trajectory of the body center of mass relative to the base of support. Model studies suggest that this requires active, feedback control, i.e., the nervous system must process sensory information on the state of the body to generate descending motor commands to the muscles to stabilize walking, especially in the mediolateral direction. Stabilization of bipedal gait is challenging and can be impaired in older and diseased individuals. In this tutorial, we illustrate how gait analysis can be used to assess the stabilizing feedback control of gait. We present methods ranging from those that require limited input data (e.g. position data of markers placed on the feet and pelvis only) to those that require full-body kinematics and electromyography. Analyses range from simple kinematics analyses to inverse dynamics. These methods assess stabilizing feedback control of human walking at three levels: 1) the level of center of mass movement and horizontal ground reaction forces, 2) the level of center of mass movement and foot placement and 3) the level of center of mass movement and the joint moments or muscle activity. We show how these can be calculated and provide a GitHub repository (https://github.com/VU-HMS/Tutorial-stabilizing-walking) which contains open access Matlab and Python code to calculate these. Finally, we discuss what information on feedback control can be learned from each of these.

The condition for dynamic stability in humans walking with feedback control

The walking human body is mechanically unstable. Loss of stability and falling is more likely in certain groups of people, such as older adults or people with neuromotor impairments, as well as in certain situations, such as when experiencing conflicting or distracting sensory inputs. Stability during walking is often characterized biomechanically, by measures based on body dynamics and the base of support. Neural control of upright stability, on the other hand, does not factor into commonly used stability measures. Here we analyze stability of human walking accounting for both biomechanics and neural control, using a modeling approach. We define a walking system as a combination of biomechanics, using the well known inverted pendulum model, and neural control, using a proportional-derivative controller for foot placement based on the state of the center of mass at midstance. We analyze this system formally and show that for any choice of system parameters there is always one periodic orbit. We then determine when this periodic orbit is stable, i.e. how the neural control gain values have to be chosen for stable walking. Following the formal analysis, we use this model to make predictions about neural control gains and compare these predictions with the literature and existing experimental data. The model predicts that control gains should increase with decreasing cadence. This finding appears in agreement with literature showing stronger effects of visual or vestibular manipulations at different walking speeds.

Effect of forward moment on recovery motion against tripping

Investigating the fall recovery motion mechanism is crucial to prevent fall injuries. Among the various parameters of motion and posture, the forward moment can be considered the representative parameter of the magnitude of tripping from a kinematic perspective. The effect of increasing the forward moment on the recovery motion after tripping was investigated in this study. A tripping experiment was performed on a treadmill, and the recovery motion was observed. The forward moment was artificially increased using several approaches, such as pulling the torso, increasing gait speed, and increasing body mass. Factor analysis was performed to establish the relationship between the recovery motion parameters and forward moment. The distribution of the factor scores implied the uniqueness of the recovery motion of the pull condition. Although the forward moment temporarily increased, it was compensated quickly. The other conditions and factors indicated qualitative similarity of the recovery motion among the different conditions. This study demonstrates that the recovery motion after tripping is robust against an increase in forward moment, regardless of the method used to increase the forward moment. The investigation of reaction motion pattern enables validation of the recovery motion and falling posture estimation. Such fall simulations will facilitate the development of a method of fall prevention and mitigation.

Mediolateral foot placement control can be trained: Older adults learn to walk more stable, when ankle moments are constrained

Falls are a problem, especially for older adults. Placing our feet accurately relative to the center-of-mass helps us to prevent falling during gait. The degree of foot placement control with respect to the center-of mass kinematic state is decreased in older as compared to young adults. Here, we attempted to train mediolateral foot placement control in healthy older adults. Ten older adults trained by walking on shoes with a narrow ridge underneath (LesSchuh), restricting mediolateral center-of-pressure shifts. As a training effect, we expected improved foot placement control during normal walking. A training session consisted of a normal walking condition, followed by a training condition on LesSchuh and finally an after-effect condition. Participants performed six of such training sessions, spread across three weeks. As a control, before the first training session, we included two similar sessions, but on normal shoes only. We evaluated whether a training effect was observed across sessions and weeks in a repeated-measures design. Whilst walking with LesSchuh, the magnitude of foot placement error reduced half-a-millimeter between sessions within a week (cohen's d = 0.394). As a training effect in normal walking, the magnitude of foot placement errors was significantly lower compared to the control week, by one millimeter in weeks 2 (cohen's d = 0.686) and 3 (cohen's d = 0.780) and by two millimeters in week 4 (cohen's d = 0.875). Local dynamic stability of normal walking also improved significantly. More precise foot placement may thus have led to improved stability. It remains to be determined whether the training effects were the result of walking on LesSchuh or from repeated treadmill walking itself. Moreover, enhancement of mechanisms beyond the scope of our outcome measures may have improved stability. At the retention test, gait stability returned to similar levels as in the control week. Yet, a reduction in foot placement error persisted.

Asymmetry measures for quantification of mechanisms contributing to dynamic stability during stepping-in-place gait

The goal of this study is to introduce and to motivate the use of new quantitative methods to improve our understanding of mechanisms that contribute to the control of dynamic balance during gait. Dynamic balance refers to the ability to maintain a continuous, oscillating center-of-mass (CoM) motion of the body during gait even though the CoM frequently moves outside of the base of support. We focus on dynamic balance control in the frontal plane or medial-lateral (ML) direction because it is known that active, neurally-mediated control mechanisms are necessary to maintain ML stability. Mechanisms that regulate foot placement on each step and that generate corrective ankle torque during the stance phase of gait are both known to contribute to the generation of corrective actions that contribute to ML stability. Less appreciated is the potential role played by adjustments in step timing when the duration of the stance and/or swing phases of gait can be shortened or lengthened to allow torque due to gravity to act on the body CoM over a shorter or longer time to generate corrective actions. We introduce and define four asymmetry measures that provide normalized indications of the contribution of these different mechanisms to gait stability. These measures are 'step width asymmetry', 'ankle torque asymmetry', 'stance duration asymmetry', and 'swing duration asymmetry'. Asymmetry values are calculated by comparing corresponding biomechanical or temporal gait parameters from adjacent steps. A time of occurrence is assigned to each asymmetry value. An indication that a mechanism is contributing to ML control is obtained by comparing asymmetry values to the ML body motion (CoM angular position and velocity) at the time points associated with the asymmetry measures. Example results are demonstrated with measures obtained during a stepping-in-place (SiP) gait performed on a stance surface that either remained fixed and level or was pseudorandomly tilted to disturb balance in the ML direction. We also demonstrate that the variability of asymmetry measures obtained from 40 individuals during unperturbed, self-paced SiP were highly correlated with corresponding coefficient of variation measures that have previously been shown to be associated with poor balance and fall risk.

High-level motor planning allows flexible walking at different gait patterns in a neuromechanical model

Humans can freely adopt gait parameters like walking speed, step length, or cadence on the fly when walking. Planned movement that can be updated online to account for changes in the environment rather than having to rely on habitual, reflexive control that is adapted over long timescales. Here we present a neuromechanical model that accounts for this flexibility by combining movement goals and motor plans on a kinematic task level with low-level spinal feedback loops. We show that the model can walk at a wide range of different gait patterns by choosing a small number of high-level control parameters representing a movement goal. A larger number of parameters governing the low-level reflex loops in the spinal cord, on the other hand, remain fixed. We also show that the model can generalize the learned behavior by recombining the high-level control parameters and walk with gait patterns that it had not encountered before. Furthermore, the model can transition between different gaits without the loss of balance by switching to a new set of control parameters in real time.

Multiple Head Rotations Result in Persistent Gait Alterations in Piglets

Multiple/repeated mild traumatic brain injury (mTBI) in young children can cause long-term gait impairments and affect the developmental course of motor control. Using our swine model for mTBI in young children, our aim was to (i) establish a reference range (RR) for each parameter to validate injury and track recovery, and (ii) evaluate changes in gait patterns following a single and multiple (5×) sagittal rapid non-impact head rotation (RNR). Gait patterns were studied in four groups of 4-week-old Yorkshire swine: healthy (n = 18), anesthesia-only sham (n = 8), single RNR injury (n = 12) and multiple RNR injury (n = 11). Results were evaluated pre-injury and at 1, 4, and 7 days post-injury. RR reliability was validated using additional healthy animals (n = 6). Repeated mTBI produced significant increases in gait time, cycle time, and stance time, as well as decreases in gait velocity and cadence, on Day One post-injury compared to pre-injury, and these remained significantly altered at Day Four and Day Seven post-injury. The gait metrics of the repeated TBI group also significantly fell outside the healthy RR on Day One, with some recovery by Day Four, while many remained altered at Day Seven. Only a bilateral decrease in hind stride length was observed at Day Four in our single RNR group compared to pre-injury. In sum, repeated and single sagittal TBI can significantly impair motor performance, and gait metrics can serve as reliable, objective, quantitative functional assessments in a juvenile porcine RNR TBI model.

The impact of unexpected platform perturbation on ankle proprioception ability in static and dynamic starting positions

AIMS

To examine the relationship between ankle proprioception and the ability to maintain balance with increased magnitudes of unexpected perturbations; and to compare the participants' ability to maintain balance following perturbations when starting from static and dynamic positions.

METHODS

Sixty physical education students (average 24.6 years) were tested for proprioception ability (AUC scores) and balance challenges presented on a perturbation treadmill. The degree at which participants lost postural balance was recorded in seven starting positions: standing-eyes-open (SO), standing-eyes-closed (SC), tandem-dominant (TD), tandem non-dominant, (TND) single-leg lateral side perturbation (SLP), single-leg medial side perturbation (SMP), and walking. Perturbation scores were analysed divided by tertiles. Multidimensional Unfolding SPSS Statistics 25 (PREFSCAL) was used to examine the relationships between data sets.

RESULTS

AUC scores of both dominant and non-dominant legs were significantly correlated with SO (r = 0.316; r = 0.445), SC (r = 0.364; r = 0.413), TD (r = 0.346; r = 0.308), and walking (r = 0.265; r = 0.439), respectively. In the dominant-leg, AUC scores of individuals with below-median SO scores were significantly worse compared to those with median SO scores (p = .046). In the non-dominant leg, individuals with above-median SC had significantly better AUC scores compared to those with lower-than-median SC (p = .008). Those with median and above-median SO and walking achieved better AUC scores than those with below-median (SO: p = .049, p = .004; walking: p = .016, p < .001, respectively). In dimension I, the SLP and SMP were located opposite one another; in dimension II, the TD and TND were located at the upper side, whereas SC, SO and walking were at the lowest side.

CONCLUSIONS

AUC scores were significantly correlated with the level at which postural balance was lost, whereby the better the proprioception ability, the better the ability to maintain balance. As such, the ability to maintain balance is harder in tandem positions than in standing and walking positions. This ability differed when perturbations were to the lateral or medial sides.

Individuals with cerebral palsy show altered responses to visual perturbations during walking

Individuals with cerebral palsy (CP) have deficits in processing of somatosensory and proprioceptive information. To compensate for these deficits, they tend to rely on vision over proprioception in single plane upper and lower limb movements and in standing. It is not known whether this also applies to walking, an activity where the threat to balance is higher. Through this study, we used visual perturbations to understand how individuals with and without CP integrate visual input for walking balance control. Additionally, we probed the balance mechanisms driving the responses to the visual perturbations. More specifically, we investigated differences in the use of ankle roll response i.e., the use of ankle inversion, and the foot placement response, i.e., stepping in the direction of perceived fall. Thirty-four participants (17 CP, 17 age-and sex-matched typically developing controls or TD) were recruited. Participants walked on a self-paced treadmill in a virtual reality environment. Intermittently, the virtual scene was rotated in the frontal plane to induce the sensation of a sideways fall. Our results showed that compared to their TD peers, the overall body sway in response to the visual perturbations was magnified and delayed in CP group, implying that they were more affected by changes in visual cues and relied more so on visual information for walking balance control. Also, the CP group showed a lack of ankle response, through a significantly reduced ankle inversion on the affected side compared to the TD group. The CP group showed a higher foot placement response compared to the TD group immediately following the visual perturbations. Thus, individuals with CP showed a dominant proximal foot placement strategy and diminished ankle roll response, suggestive of a reliance on proximal over distal control of walking balance in individuals with CP.

Backward Locomotor Treadmill Training Differentially Improves Walking Performance across Stroke Walking Impairment Levels

Background: Post-stroke walking impairment is a significant cause of chronic disability worldwide and often leads to loss of life roles for survivors and their caregivers. Walking impairment is traditionally classified into mild (>0.8 m/s), moderate (0.41–0.8 m/s), and severe (≤0.4 m/s), and those categorized as “severe” are more likely to be homebound and at greater risk of falls, fractures, and rehospitalization. In addition, there are minimal effective walking rehabilitation strategies currently available for this subgroup. Backward locomotor treadmill training (BLTT) is a novel and promising training approach that has been demonstrated to be safe and feasible across all levels of impairment; however, its benefits across baseline walking impairment levels (severe (≤0.4 m/s) vs. mild–moderate (>0.4 m/s)) have not been examined. Methods: Thirty-nine adults (>6 months post-stroke) underwent 6 days of BLTT (3×/week) over 2 weeks. Baseline and PRE to POST changes were measured during treadmill training and overground walking. Results: Individuals with baseline severe walking impairment were at a more significant functional disadvantage across all spatiotemporal walking measures at baseline and demonstrated fewer overall gains post-training. However, contrary to our working hypothesis, both groups experienced comparable increases in cadence, bilateral percent single support times, and step lengths. Conclusion: BLTT is well tolerated and beneficial across all walking impairment levels, and baseline walking speed (≤0.4 m/s) should serve as a covariate in the design of future walking rehabilitation trials.

Ankle muscles drive mediolateral center of pressure control to ensure stable steady state gait

During steady-state walking, mediolateral gait stability can be maintained by controlling the center of pressure (CoP). The CoP modulates the moment of the ground reaction force, which brakes and reverses movement of the center of mass (CoM) towards the lateral border of the base of support. In addition to foot placement, ankle moments serve to control the CoP. We hypothesized that, during steady-state walking, single stance ankle moments establish a CoP shift to correct for errors in foot placement. We expected ankle muscle activity to be associated with this complementary CoP shift. During treadmill walking, full-body kinematics, ground reaction forces and electromyography were recorded in thirty healthy participants. We found a negative relationship between preceding foot placement error and CoP displacement during single stance; steps that were too medial were compensated for by a lateral CoP shift and vice versa, steps that were too lateral were compensated for by a medial CoP shift. Peroneus longus, soleus and tibialis anterior activity correlated with these CoP shifts. As such, we identified an (active) ankle strategy during steady-state walking. As expected, absolute explained CoP variance by foot placement error decreased when walking with shoes constraining ankle moments. Yet, contrary to our expectations that ankle moment control would compensate for constrained foot placement, the absolute explained CoP variance by foot placement error did not increase when foot placement was constrained. We argue that this lack of compensation reflects the interdependent nature of ankle moment and foot placement control. We suggest that single stance ankle moments do not only compensate for preceding foot placement errors, but also assist control of the subsequent foot placement. Foot placement and ankle moment control are 'caught' in a circular relationship, in which constraints imposed on one will also influence the other.

Immersive Virtual Reality and Vestibular Rehabilitation in Multiple Sclerosis: Case Report

Background

Dizziness and imbalance are common and disabling symptoms in patients with multiple sclerosis (MS) and are caused by a central, peripheral, or mixed vestibulopathy. Central vestibular disorder is the most frequently reported vestibular problem in the MS population due to demyelination. Vestibular rehabilitation ameliorates these symptoms and their repercussions and improves quality of life. Immersive virtual reality (VRi) is an emerging tool in this field; however, no previous research has been performed studying its effects in MS.

Objective

The aim of this study was to apply a VRi vestibular training protocol to a patient with MS and assess the effects induced by the experimental intervention.

Methods

This case study included a 54-year-old woman with relapsing-remitting MS. We developed a standardized VRi exercise protocol for vestibular rehabilitation based on the gold-standard Cawthorne-Cooksey vestibular training protocol. The 20-session intervention was made up of 10 initial sessions and 10 advanced sessions. Each 50-minute session was performed two to three times per week for 7 weeks. Four evaluations were carried out over the study period: at baseline (T0), between initial and advances phases (T1), postintervention (T2), and 1 month after the experimental procedure (T3). The research outcomes were dizziness, balance, gait, impact of fatigue, quality of life, repercussions in muscular tone, and usability of the head-mounted display device.

Results

After implementing the VRi vestibular protocol, improvements were seen in the following patient parameters: Dizziness Handicap Inventory score (62 points at T0; 4 points at T2); Berg Balance Scale score (47 points at T0; 54 points at T2); instrumented Timed Up and Go time (8.35 seconds at T0; 5.57 seconds at T2); muscular tone of the erector spinae, rectus femoris, and soleus; Modified Fatigue Impact Scale score (61 points at T0; 37 points at T2); and Multiple Sclerosis Quality of Life-54 values (67.16% in the physical health area at T2; 33.56% in the mental health area at T2). The patient rated the usability of the system as 90%, based on the System Usability Scale, and gave the system a grade of A.

Conclusions

Although further research is needed, this study provided initial evidence that the first VRi vestibular protocol for the MS population can improve dizziness, balance, gait, impact of fatigue, quality of life, and muscular tone through an exergame intervention. This study may help establish a standardized VRi protocol for vestibular rehabilitation.

A review of musculoskeletal modelling of human locomotion

Locomotion through the environment is important because movement provides access to key resources, including food, shelter and mates. Central to many locomotion-focused questions is the need to understand internal forces, particularly muscle forces and joint reactions. Musculoskeletal modelling, which typically harnesses the power of inverse dynamics, unites experimental data that are collected on living subjects with virtual models of their morphology. The inputs required for producing good musculoskeletal models include body geometry, muscle parameters, motion variables and ground reaction forces. This methodological approach is critically informed by both biological anthropology, with its focus on variation in human form and function, and mechanical engineering, with a focus on the application of Newtonian mechanics to current problems. Here, we demonstrate the application of a musculoskeletal modelling approach to human walking using the data of a single male subject. Furthermore, we discuss the decisions required to build the model, including how to customize the musculoskeletal model, and suggest cautions that both biological anthropologists and engineers who are interested in this topic should consider.

Interactions Between Different Age-Related Factors Affecting Balance Control in Walking

Maintaining balance during walking is a continuous sensorimotor control problem. Throughout the movement, the central nervous system has to collect sensory data about the current state of the body in space, use this information to detect possible threats to balance and adapt the movement pattern to ensure stability. Failure of this sensorimotor loop can lead to dire consequences in the form of falls, injury and death. Such failures tend to become more prevalent as people get older. While research has established a number of factors associated with higher risk of falls, we know relatively little about age-related changes of the underlying sensorimotor control loop and how such changes are related to empirically established risk factors. This paper approaches the problem of age-related fall risk from a neural control perspective. We begin by summarizing recent empirical findings about the neural control laws mapping sensory input to motor output for balance control during walking. These findings were established in young, neurotypical study populations and establish a baseline of sensorimotor control of balance. We then review correlates for deteriorating balance control in older adults, of muscle weakness, slow walking, cognitive decline, and increased visual dependency. While empirical associations between these factors and fall risk have been established reasonably well, we know relatively little about the underlying causal relationships. Establishing such causal relationships is hard, because the different factors all co-vary with age and are difficult to isolate empirically. One option to analyze the role of an individual factor for balance control is to use computational models of walking comprising all levels of the sensorimotor control loop. We introduce one such model that generates walking movement patterns from a short list of spinal reflex modules with limited supraspinal modulation for balance. We show how this model can be used to simulate empirical studies, and how comparison between the model and empirical results can indicate gaps in our current understanding of balance control. We also show how different aspects of aging can be added to this model to study their effect on balance control in isolation.

Using force data to self-pace an instrumented treadmill and measure self-selected walking speed

BACKGROUND

Self-selected speed is an important functional index of walking. A self-pacing controller that reliably matches walking speed without additional hardware can be useful for measuring self-selected speed in a treadmill-based laboratory.

METHODS

We adapted a previously proposed self-pacing controller for force-instrumented treadmills and validated its use for measuring self-selected speeds. We first evaluated the controller's estimation of subject speed and position from the force-plates by comparing it to those from motion capture data. We then compared five tests of self-selected speed. Ten healthy adults completed a standard 10-meter walk test, a 150-meter walk test, a commonly used manual treadmill speed selection test, a two-minute self-paced treadmill test, and a 150-meter self-paced treadmill test. In each case, subjects were instructed to walk at or select their comfortable speed. We also assessed the time taken for a trial and a survey on comfort and ease of choosing a speed in all the tests.

RESULTS

The self-pacing algorithm estimated subject speed and position accurately, with root mean square differences compared to motion capture of 0.023 m s -1 and 0.014 m, respectively. Self-selected speeds from both self-paced treadmill tests correlated well with those from the 10-meter walk test (R>0.93,p<1×10-13). Subjects walked slower on average in the self-paced treadmill tests (1.23±0.27 ms-1) than in the 10-meter walk test (1.32±0.18 ms-1) but the speed differences within subjects were consistent. These correlations and walking speeds are comparable to those from the manual treadmill speed selection test (R=0.89,p=3×10-11;1.18±0.24 ms-1). Comfort and ease of speed selection were similar in the self-paced tests and the manual speed selection test, but the self-paced tests required only about a third of the time to complete. Our results demonstrate that these self-paced treadmill tests can be a strong alternative to the commonly used manual treadmill speed selection test.

CONCLUSIONS

The self-paced force-instrumented treadmill well adapts to subject walking speed and reliably measures self-selected walking speeds. We provide the self-pacing software to facilitate use by gait researchers and clinicians.