Persistent and anti-persistent pattern in stride-to-stride variability of treadmill walking: influence of rhythmic auditory cueing

Novel possibilities of acceleration time series for performance and acute fatigue assessment in uphill trail running

The potential for assessing performance and acute fatigue in uphill trail running (UTR) through acceleration time series remains underexplored. For this purpose, time-variability of body acceleration and covariation among limb acceleration were studied in UTR. Twenty competitive and young trail runners participated in a simulation UTR test covering a distance of 4758 meters, with a total elevation gain of 575 meters and an average slope of 13.6%. Four sections with clear slope differences were identified. Detrended Fluctuation Analysis of upper back acceleration and Principal Component Analysis among wrists and ankle acceleration were performed for the whole test and for each section.The outcomes were correlated with performance and standardized effect size was used to compare sections. The main findings suggest that (a) runners with higher performance showed less persistence in body acceleration fluctuations and greater interlimb diversity, and (b) the steepest parts, particularly the final and effortful section, showed increased persistence in body acceleration and some runners lost interlimb covariation.In conclusion, time-variability and coordination analyses of acceleration time series seem to be sensitive to performance and acute fatigue in UTR, which opens further possibilities for providing more integrative, dynamic, and practical assessment tools.

Validity of Linear and Nonlinear Measures of Gait Variability to Characterize Aging Gait with a Single Lower Back Accelerometer

The attractor complexity index (ACI) is a recently developed gait analysis tool based on nonlinear dynamics. This study assesses ACI's sensitivity to attentional demands in gait control and its potential for characterizing age-related changes in gait patterns. Furthermore, we compare ACI with classical gait metrics to determine its efficacy relative to established methods. A 4 × 200 m indoor walking test with a triaxial accelerometer attached to the lower back was used to compare gait patterns of younger (N = 42) and older adults (N = 60) during normal and metronome walking. The other linear and non-linear gait metrics were movement intensity, gait regularity, local dynamic stability (maximal Lyapunov exponents), and scaling exponent (detrended fluctuation analysis). In contrast to other gait metrics, ACI demonstrated a specific sensitivity to metronome walking, with both young and old participants exhibiting altered stride interval correlations. Furthermore, there was a significant difference between the young and old groups (standardized effect size: -0.77). Additionally, older participants exhibited slower walking speeds, a reduced movement intensity, and a lower gait regularity. The ACI is likely a sensitive marker for attentional load and can effectively discriminate age-related changes in gait patterns. Its ease of measurement makes it a promising tool for gait analysis in unsupervised (free-living) conditions.

Monitoring Age-Related Changes in Gait Complexity in the Wild with a Smartphone Accelerometer System

Stride-to-stride fluctuations during walking reflect age-related changes in gait adaptability and are estimated with nonlinear measures that confine data collection to controlled settings. Smartphones, with their embedded accelerometers, may provide accessible gait analysis throughout the day. This study investigated age-related differences in linear and nonlinear gait measures estimated from a smartphone accelerometer (SPAcc) in an unconstrained, free-living environment. Thirteen young adults (YA) and 11 older adults (OA) walked within a shopping mall with a SPAcc placed in their front right pants pocket. The inter-stride interval, calculated as the time difference between ipsilateral heel contacts, was used for dependent measures calculations. One-way repeated-measures analysis of variance revealed significant (p < 0.05) age-related differences (mean: YA, OA) for stride-time standard deviation (0.04 s, 0.05 s) and coefficient of variation (3.47%, 4.16%), sample entropy (SaEn) scale 1 (1.70, 1.86) and scale 3 (2.12, 1.80), and statistical persistence decay (31 strides, 23 strides). The fractal scaling index was not different between groups (0.93, 0.95), but exceeded those typically found in controlled settings, suggesting an upregulation in adaptive behaviour likely to accommodate the increased challenge of free-living walking. These findings support the SPAcc as a viable telehealth instrument for remote monitoring of gait dynamics, with implications for unsupervised fall-risk assessment.

A model of task-level human stepping regulation yields semistable walking

A simple lateral dynamic walker, with swing leg dynamics and three adjustable input parameters, is used to study how motor regulation affects frontal-plane stepping. Motivated by experimental observations and phenomenological models, we imposed task-level multi-objective regulation targeting the walker's optimal lateral foot placement at each step. The regulator prioritizes achieving step width and lateral body position goals to varying degrees by choosing a mixture parameter. Our model thus integrates a lateral mechanical template, which captures the fundamental mechanics of frontal-plane walking, with a lateral motor regulation template, an empirically verified model of how humans manipulate lateral foot placements in a goal-directed manner. The model captures experimentally observed stepping fluctuation statistics and demonstrates how linear empirical models of stepping dynamics can emerge from first-principles nonlinear mechanics. We find that task-level regulation gives rise to a goal-equivalent manifold in the system's extended state space of mechanical states and inputs, a subset of which contains a continuum of period-1 gaits forming a semistable set: perturbations off of any of its gaits result in transients that return to the set, though typically to different gaits.

Validation of Linear and Nonlinear Gait Variability Measures Derived From a Smartphone System Compared to a Gold-Standard Footswitch System During Overground Walking

Smartphones, with embedded accelerometers, may be a viable method to monitor gait variability in the free-living environment. However, measurements estimated using smartphones must first be compared to known quantities to ensure validity. This study assessed the validity and reliability of smartphone-derived gait measures compared to a gold-standard footswitch system during overground walking. Seventeen adults completed three 8-minute overground walking trials during 3 separate visits. The stride time series was calculated as the time difference between consecutive right heel contact events within the footswitch and smartphone-accelerometry signals. Linear (average stride time, stride time standard deviation, and stride time coefficient of variation) and nonlinear (fractal scaling index, approximate entropy, and sample entropy) measures were calculated for each stride time series. Bland-Altman plots with 95% limits of agreement assessed agreement between systems. Intraclass correlation coefficients assessed reliability across visits. Bland-Altman plots revealed acceptable limits of agreement for all measures. Intraclass correlation coefficients revealed good-to-excellent reliability for both systems, except for fractal scaling index, which was moderate. The smartphone system is a valid method and performs similarly to gold-standard research equipment. These findings suggest the development and implementation of an inexpensive, easy-to-use, and ubiquitous telehealth instrument that may replace traditional laboratory equipment for use in the free-living environment.

The repeatability of stride time variability, regularity, and long-range correlations

BACKGROUND

Detrended fluctuation analysis (DFA) and sample entropy (SE) measure the long-term correlations and regularity of gait patterns, respectively, having previously been used to identify participants at risk of falling, previous history of injury, or patients with motor diseases. Since these measures are more sensitive to gait impairment than linear measures (e.g., the standard deviation [SD] of stride time), they can be potentially used in military medicine to identify soldiers at risk of injury. However, clinometric properties are yet to be established.

RESEARCH QUESTION

What is the repeatability of DFA, SE, and traditional linear measures of stride time variability (SD and coefficient of variation [CV]) under various load and speed constraints?

METHODS

Fourteen Australian Army trainee soldiers (age: 25.6 ± 5.9 y, height: 1.74 ± 0.08 m, body mass: 77.2 ± 15.1 kg, service: 1.5 ± 1.8 y) attended three sessions over two weeks, completing four 12-minute walking trials on an instrumented treadmill in each session. Participants walked with a combination of 0 kg or 23 kg loads at a self-selected or 5.5 km/h speed. Heel contacts from the right foot were identified using treadmill-embedded force plates. From 512 stride time intervals, linear (SD and CV), and non-linear (DFA and SE) measures were obtained. To assess the between-session repeatability, intraclass correlations (ICC 2,1) were employed.

RESULTS AND SIGNIFICANCE

There was poor-to-moderate repeatability for the SD (ICC: 0.357-0.545) and CV (ICC: 0.371-0.529). DFA showed poor-to-moderate repeatability (ICC: 0.013-0.504), while SE had poor repeatability (ICC: 0.133-0.226). Previous studies have shown that differences of > 0.19 in DFA and > 0.66 in SE can differentiate between healthy and pathological gait. These values are greater than this study's reported standard error of measurement, indicating that clinically meaningful changes may still be detectable despite low repeatability.

A model of task-level human stepping regulation yields semistable walking

A simple lateral dynamic walker, with swing leg dynamics and three adjustable input parameters, is used to study how motor regulation affects frontal plane stepping. Motivated by experimental observations and phenomenological models, we imposed task-level multiobjective regulation targeting the walker's optimal lateral foot placement at each step. The regulator prioritizes achieving step width and lateral body position goals to varying degrees by choosing a mixture parameter. Our model thus integrates a lateral mechanical template, which captures fundamental mechanics of frontal-plane walking, with a lateral motor regulation template, an empirically verified model of how humans manipulate lateral foot placements in a goal-directed manner. The model captures experimentally observed stepping fluctuation statistics and demonstrates how linear empirical models of stepping dynamics can emerge from first-principles nonlinear mechanics. We find that task-level regulation gives rise to a goal equivalent manifold in the system's extended state space of mechanical states and inputs, a subset of which contains a continuum of period-1 gaits forming a semistable set: perturbations off of any of its gaits result in transients that return to the set, though typically to different gaits.

Effects of metronome walking on long-term attractor divergence and correlation structure of gait: a validation study in older people

This study investigates the effects of metronome walking on gait dynamics in older adults, focusing on long-range correlation structures and long-range attractor divergence (assessed by maximum Lyapunov exponents). Sixty older adults participated in indoor walking tests with and without metronome cues. Gait parameters were recorded using two triaxial accelerometers attached to the lumbar region and to the foot. We analyzed logarithmic divergence of lumbar acceleration using Rosenstein's algorithm and scaling exponents for stride intervals from foot accelerometers using detrended fluctuation analysis (DFA). Results indicated a concomitant reduction in long-term divergence exponents and scaling exponents during metronome walking, while short-term divergence remained largely unchanged. Furthermore, long-term divergence exponents and scaling exponents were significantly correlated. Reliability analysis revealed moderate intrasession consistency for long-term divergence exponents, but poor reliability for scaling exponents. Our results suggest that long-term divergence exponents could effectively replace scaling exponents for unsupervised gait quality assessment in older adults. This approach may improve the assessment of attentional involvement in gait control and enhance fall risk assessment.

Gait variability, fractal dynamics, and statistical regularity of treadmill and overground walking recorded with a smartphone

BACKGROUND

The nonlinear variability present during steady-state gait may provide a signature of health and showcase one's walking adaptability. Although treadmills can capture vast amounts of walking data required for estimating variability within a small space, gait patterns may be misrepresented compared to an overground setting. Smartphones may provide a low-cost and user-friendly estimate of gait patterns among a variety of walking settings. However, no study has investigated differences in gait patterns derived from a smartphone between treadmill walking (TW) and overground walking (OW).

RESEARCH QUESTION

This study implemented a smartphone accelerometer to compare differences in temporal gait variability and gait dynamics between TW and OW.

METHODS

Sixteen healthy adults (8F; 24.7 ± 3.8 years) visited the laboratory on three separate days and completed three 8-minute OW and three TW trials, at their preferred speed, during each visit. The inter-stride interval was calculated as the time difference between right heel contact events located within the vertical accelerometery signals recorded from a smartphone while placed in participants front right pant pocket during walking trials. The inter-stride interval series was used to calculate stride time standard deviation (SD) and coefficient of variation (COV), statistical persistence (fractal scaling index), and statistical regularity (sample entropy). Two-way analysis of variance compared walking condition and laboratory visits for each measure.

RESULTS

Compared to TW, OW displayed significantly (p < 0.01) greater stride time SD (0.014 s, 0.020 s), COV (1.26 %, 1.82 %), fractal scaling index (0.70, 0.79) and sample entropy (1.43, 1.63). No differences were found between visits for all measures.

SIGNIFICANCE

Smartphone-based assessment of gait provides the ability to distinguish between OW and TW conditions, similar to previously established methodologies. Furthermore, smartphones may be a low-cost and user-friendly tool to estimate gait patterns outside the laboratory to improve ecological validity, with implications for free-living monitoring of gait among various populations.

Application of vibration to the soles increases long-range correlations in the stride parameters during walking

Temporal fluctuations in the stride parameters during human walking exhibit long-range correlations, but these long-range correlations in the stride parameters decrease due to aging or neuromuscular diseases. These observations suggest that any quantified index of the long-range correlation can be regarded as an indicator of gait functionality. Considering the effect of task-relevant sensory feedback on augmenting human motor performance, we devised shoes with active insoles that could deliver noisy vibration to the soles of feet and assessed their efficacy in enhancing the long-range correlations in the stride parameters for healthy young adults. The vibration could be wirelessly controlled using a smartphone. The actuators, control unit, and battery in the devised shoes were light and embedded in the shoes. By virtue of this compactness, the shoes could be easily used for daily walking outside a laboratory. We performed walking experiments with 20 healthy adults and evaluated the effects of sub- and supra-threshold vibration on long-range correlations in stride interval and length. We performed detrended fluctuation analysis to quantify the long-range correlation of temporal changes in stride interval and length. We found that supra-threshold vibration, applied to the soles with the amplitude of 130 % of the sensory threshold, significantly increased the long-range correlations in stride interval and length by 10.3 % (p = 0.009) and 10.1 % (p = 0.021), respectively. On the other hand, sub-threshold vibration with the amplitude of 90 % of the sensory threshold had no significant effect. These results demonstrate that additional somatosensory feedback through barely detectable vibrations, which are supplied by compact shoes with active insoles, can enhance the indices of "healthy" complexity of locomotor function.

Evaluation of a smartphone accelerometer system for measuring nonlinear dynamics during treadmill walking: Concurrent validity and test-retest reliability

The accelerometers embedded within smartphones may be a promising tool to capture gait patterns outside the laboratory and for extended periods of time. The current study evaluated the agreement and reliability of gait measures derived from a smartphone accelerometer system, compared to reference motion capture and footswitch systems during treadmill walking. Seventeen healthy young adults visited the laboratory on three separate days and completed three 8-minute treadmill walking trials, during each visit, at their preferred walking speed. The inter-stride interval series was calculated as the time difference between consecutive right heel contacts, located within the signals of the smartphone accelerometer, motion capture, and footswitch systems. The inter-stride interval series was used to estimate common linear gait measures and nonlinear measures, including fractal scaling index, approximate entropy, and sample entropy. Bland Altman plots with 95% limits of agreement and intraclass correlation coefficients assessed agreement and reliability, respectively. The smartphone system was found to be within the acceptable limits of agreement when compared to either reference system. The intraclass correlation coefficients values revealed moderate-to-excellent reliability for the smartphone system, with greater reliability found for linear compared to nonlinear measures and were similar to both reference systems, except for the fractal scaling index. These findings suggest the smartphone accelerometer system is a valid and reliable method for estimating linear and nonlinear gait measures during treadmill walking.

Model of Gait Control in Parkinson's Disease and Prediction of Robotic Assistance

Gait variability of healthy adults exhibits Long-Range Autocorrelations (LRA), meaning that the stride interval at any time statistically depends on previous gait cycles; and this dependency spans over several hundreds of strides. Previous works have shown that this property is altered in patients with Parkinson's disease, such that their gait pattern corresponds to a more random process. Here, we adapted a model of gait control to interpret the reduction in LRA that characterized patients in a computational framework. Gait regulation was modeled as a Linear-Quadratic-Gaussian control problem where the objective was to maintain a fixed velocity through the coordinated regulation of stride duration and length. This objective offers a degree of redundancy in the way the controller can maintain a given velocity, resulting in the emergence of LRA. In this framework, the model suggested that patients exploited less the task redundancy, likely to compensate for an increased stride-to-stride variability. Furthermore, we used this model to predict the potential benefit of an active orthosis on the gait pattern of patients. The orthosis was embedded in the model as a low-pass filter on the series of stride parameters. We show in simulations that, with a suitable level of assistance, the orthosis could help patients recovering a gait pattern with LRA comparable to that of healthy controls. Assuming that the presence of LRA in a stride series is a marker of healthy gait control, our study provides a rationale for developing gait assistance technology to reduce the fall risk associated with Parkinson's disease.

Assessing proprioception through time-variability properties of acceleration

Proprioception is a crucial property for movement stability and balance, but its current assessment, based on clinical testing, lacks precision and adequacy in real contexts. This study proposes assessing proprioception and its sensitivity to training effects through acceleration time series recorded during two slackline experiments. In the first experiment, slackliners of different expertise (highly and poorly trained) had to walk on a slackline for 30 s. In the second, twelve beginners had to balance up on the slackline for at least 11 s before and after a training process. Acceleration time series were recorded in body components (legs and centre of mass) and the slackline. The acceleration fluctuations were analysed through Detrended Fluctuation Analysis. The obtained Hurst (H)-exponents were compared between both groups (first experiment) and before and after training (second experiment) using Whitney and Wilcoxon tests, respectively. The values of H-exponents were lower in the highly trained group (Z = -2.15, p = 0.03) (first experiment), and in the post-training conditions (Z = -2.35, p = 0.02) (second experiment). These results suggest better motor and proprioceptive control with training status. Hence, the time-variability structure of acceleration in real contexts, like slackline tasks, is proposed as an objective measure of proprioception and its training effects.

Stride-to-stride time intervals are independently affected by the temporal pattern and probability distribution of visual cues

The temporal structure of the variability of the stride-to-stride time intervals during paced walking is affected by the underlying autocorrelation function (ACF) of the pacing signal. This effect could be accounted for by differences in the underlying probability distribution function (PDF) of the pacing signal. We investigated the isolated and combined effect of the ACF and PDF of the pacing signals on the temporal structure of the stride-to-stride time intervals during visually guided paced overground walking. Ten young, healthy participants completed four walking trials while synchronizing their footstep to a visual pacing signal with a temporal pattern of either pink or white noise (different ACF) and either a Gaussian or normal probability distribution (different PDF). The scaling exponent from the Detrended Fluctuation Analysis was used to quantify the temporal structure of the stride-to-stride time intervals. The ACF and PDF of the pacing signals had independent effects on the scaling exponent of the stride-to-stride time intervals. The scaling exponent was higher during the pink noise pacing trials compared to the white noise pacing trials and higher during the trials with the Gaussian probability distribution compared to the uniform distribution. The results suggest that the sensorimotor system in healthy young individuals has an affinity towards external cues with a pink noise pattern and a Gaussian probability distribution during paced walking.

Adiabatic Invariant of Center-of-Mass Motion during Walking as a Dynamical Stability Constraint on Stride Interval Variability and Predictability

Simple Summary

Human walking exhibits properties of both stability and variability. On the one hand, the variability of the interval of time between heel strikes is autocorrelated, i.e., not randomly organized. On the other hand, walking is highly stereotyped and arguments from general mechanics suggest that the stability of gait can be assessed according to invariant properties. This study aims at proposing one of those invariants. Participants walked for 10 min at a natural pace, with and without a metronome indicating participants’ preferred step frequency. In both cases, we use different parameters to assess both the variability and stability of walking. We verify a known result: the metronome strongly alters the variability of the motion. However, despite the large variability changes, our proposed adiabatic invariant is preserved in both conditions, demonstrating the stability of gait. It appears as though our model reveals dynamical constraints that are “hidden” beyond apparent walking variability.

Abstract

Human walking exhibits properties of global stability, and local dynamic variability, predictability, and complexity. Global stability is typically assessed by quantifying the whole-body center-of-mass motion while local dynamic variability, predictability, and complexity are assessed using the stride interval. Recent arguments from general mechanics suggest that the global stability of gait can be assessed with adiabatic invariants, i.e., quantities that remain approximately constant, even under slow external changes. Twenty-five young healthy participants walked for 10 min at a comfortable pace, with and without a metronome indicating preferred step frequency. Stride interval variability was assessed by computing the coefficient of variation, predictability using the Hurst exponent, and complexity via the fractal dimension and sample entropy. Global stability of gait was assessed using the adiabatic invariant computed from averaged kinetic energy value related to whole-body center-of-mass vertical displacement. We show that the metronome alters the stride interval variability and predictability, from autocorrelated dynamics to almost random dynamics. However, despite these large local variability and predictability changes, the adiabatic invariant is preserved in both conditions, showing the global stability of gait. Thus, the adiabatic invariant theory reveals dynamical global stability constraints that are “hidden” behind apparent local walking variability and predictability.

Persistence and anti-persistence in treadmill walking

BACKGROUND

Strong, long-range persistent correlations in stride time (ST) and length (SL) are the fundamental traits of treadmill gait. Our recent work showed that the ST and SL time series' statistical properties originated from the superposition of large-scale trends and small-scale fluctuations (residuals). Trends served as the control manifolds about which ST and SL fluctuated.

RESEARCH QUESTION

Do random changes in treadmill belt speed affect the trend properties and ST/SL scaling exponents?

METHODS

We used Multivariate Adaptive Regression Splines (MARS) to determine gait trends during a walk on a treadmill whose belt speed was perturbed by a strong random noise (coefficient of variation was equal to 0.075, 0.1, and 0.13 for treadmill speed 0.8 m/s, 1.2 m/s, and 1.6 m/s, respectively). Then, we calculated the ST/SL scaling exponents of the experimental time series and the corresponding MARS residuals with the madogram estimator.

RESULTS

Except for the ST at the lowest treadmill speed, the normalized trend duration was at least two times greater than that for the unperturbed walk. The Cauchy distribution scale parameter, which served as a measure of the width of SL and ST trend slope distributions, was at v=1.2m/s, almost 50% and 25% smaller than the unperturbed values. The differences were even greater at v=1.6 m/s: 73% and 83%. Apart from ST at v=0.8m/s, the ST/SL scaling indices were close to 0.5. For all speeds, the ST and SL MARS residuals were strongly anti-persistent. At v=1.2m/s, the corresponding scaling exponents were equal to 0.37±0.10 and 0.25±0.09.

SIGNIFICANCE

At normal and moderate treadmill speeds, in the presence of random belt speed perturbations, strongly anti-persistent fluctuations about gentle, persistent trends can lead to weak persistence/antipersistence of ST/SL time series.

The temporal pattern and the probability distribution of visual cueing can alter the structure of stride-to-stride variability

The structure of the stride-to-stride time intervals during paced walking can be altered by the temporal pattern of the pacing cues, however, it is unknown if an altered probability distribution of these cues could also affect stride-to-stride time intervals. We investigated the effect of the temporal pattern and probability distribution of visual pacing cues on the temporal structure of the variability of the stride-to-stride time intervals during walking. Participants completed self-paced walking (SPW) and walking paced by visual cueing that had a temporal pattern of either pink noise presented with a normal distribution (PNND), shuffled pink noise presented with a normal distribution (SPNND), white noise presented with a normal distribution (WNND), and white noise presented with a uniform distribution (WNUD). The temporal structure of the stride-to-stride time intervals was quantified using the scaling exponent calculated from Detrended Fluctuation Analysis. The scaling exponent was higher during the SPW and PNND trials than during the SPNND, WNND and WNUD trials and it was lower during the WNUD trial compared to the SPNND trial. The results revealed that both the temporal pattern and the probability distribution of the visual pacing cues can affect the scaling exponent of the variability of the stride-to-stride time intervals. This information is fundamental in understanding how visual input is involved in the control of gait.

Effects of acoustically paced cadence modulation on impact forces in running

BACKGROUND

Increasing cadence in running has been advocated as a means to improve performance and reduce impact forces. Although acoustic pacing can be used for this purpose, it might by itself lead to an increased impact force, which would counteract the decrease in impact force that is being pursued by increasing the cadence with acoustic pacing and thus have a counterproductive effect.

RESEARCH QUESTION

What are the effects of acoustic pacing and cadence on peak impact force and loading rate during running?

METHODS

Unpublished data from a previous study, in which 16 participants ran on an instrumented treadmill with various forms of acoustic pacing, were analyzed to address the research question. Peak impact force and loading rate while running with and without pacing, at three different cadences were extracted from the ground reaction force data and compared statistically between these two main conditions. In addition, we compared step-based and stride-based pacing, and paced and unpaced steps within stride-based pacing conditions.

RESULTS

As expected, increasing the cadence was accompanied by a significant reduction in peak impact force and instantaneous vertical loading rate, whereas acoustic pacing had no significant effect on the impact forces compared to unpaced running with similar cadence, both before and after pacing. There were also no significant differences in this regard between step-based and stride-based pacing.

SIGNIFICANCE

Acoustic pacing does not adversely affect impact force when used to increase cadence in running with the aim of reducing the impact force and can thus be used for this purpose without introducing a counterproductive effect.

Examining feedback mechanisms of postural control in Chiari Malformation by average wavelet coefficient decomposition and the Hurst exponent

BACKGROUND

Chiari Malformation (CM) is a congenital disorder occurring when the cerebellar tonsils descend into the foramen magnum, inhibiting cerebrospinal fluid (CSF) flow, causing headaches, dizziness, difficulty swallowing, muscle weakness, and loss of neuromuscular coordination. While there is no cure, surgical decompression of the hindbrain is used to alleviate symptoms. Loss of postural control is a main symptom reported by these patients; however, no study has examined postural stability in this cohort of patients.

RESEARCH QUESTION

Do patients with CM exhibit impaired postural stability compared to healthy controls?.

METHODS

Twelve female participants diagnosed with CM performed a postural stability test where six participants had undergone decompression (CM-D) surgery while six had not (CM-ND). Participants stood in Romberg fashion on an AMTI force plate according to an IRB-approved protocol. Postural stability measures were quantified by computing Hurst exponents. These values were determined from the Average Wavelet Coefficient method using a level 12 Symlet-2 wavelet to analyze anterior-posterior (AP) center-ofpressure (COP) trajectories in MATLAB. Identical procedures and analyses were performed on healthy control participants with no known neuromuscular disorders.

RESULTS

CM participants displayed significantly impaired postural stability compared to healthy controls (p = 0.0002). CM-D participants displayed significantly impaired postural stability compared to CM-ND (p = 0.002). CM-D and CM-ND both displayed significantly impaired postural stability compared to controls (p < 0.0001 and p < 0.003, respectively).

SIGNIFICANCE

Loss of postural stability is considered a main symptom of CM, however no study has previously quantified human postural control in this cohort of patients. Quantifying this relationship can provide further insight to neurologists studying the disorder and to therapists planning rehabilitation and pain relief methods.

Walking humans trade off different task goals to regulate lateral stepping

People walk in complex environments where they must adapt their steps to maintain balance and satisfy changing task goals. How people do this is not well understood. We recently developed computational models of lateral stepping, based on Goal Equivalent Manifolds that serve as motor regulation templates, to identify how people regulate walking movements from step-to-step. In normal walking, healthy adults strongly maintain step width, but also lateral position on their path. Here, we used this framework to pose empirically-testable hypotheses about how humans might adapt their lateral stepping dynamics when asked to prioritize different stepping goals. Participants walked on a treadmill in a virtual-reality environment under 4 conditions: normal walking and, while given direct feedback at each step, walking while trying to maintain constant step width, constant absolute lateral position, or constant heading (direction). Time series of lateral stepping variables were extracted, and variability and statistical persistence (reflecting step-to-step regulation) quantified. Participants exhibited less variability of the prescribed stepping variable compared to normal walking during each feedback condition. Stepping regulation results supported our models' predictions: to maintain constant step width or position, people either maintained or increased regulation of the prescribed variable, but also decreased regulation of its complement. Thus, people regulated lateral foot placements in predictable and systematic ways determined by specific task goals. Humans regulate stepping movements to not only "just walk" (step without falling), but also to achieve specific goal-directed tasks within a specific environment. The framework and motor regulation templates presented here capture these important interactions.

Effect of Short-Term Metro-Rhythmic Stimulations on Gait Variability

The aim of the study was to define the effect of different short-term metro-rhythmic stimulations on the time and spatial parameters of gait. The secondary goal was to test whether prior instructions on how to respond to stimulations played a significant role in the stimulation by sound stimuli. Experimental tests of gait were conducted on a group of 36 healthy participants: group 1—subjects who were not informed how to react after hearing sound stimuli, group 2—subjects who received a clear instruction before the test to adjust the frequency of taking steps to the rhythm of the music. The gait research was carried out on a Zebris FDM-S (zebris Medical Gmbh, Isny, Germany) treadmill for various sound stimuli (arrhythmic stimulus, rhythmic stimuli at different rate). It was shown that a short-term influence of metro-rhythmic stimulations changes the time and spatial parameters of gait, i.e., gait frequency, length and duration of the gait cycle. The greatest impact on the modification of the time–space parameters of walking is exerted by rhythmic stimuli at a pace different from the frequency of gait at a preferred velocity. Providing information on how to respond to sounds heard may be important in gait therapy with RAS (rhythmic auditory stimulation).

How persons with transtibial amputation regulate lateral stepping while walking in laterally destabilizing environments

BACKGROUND

Persons with lower limb amputation often experience decreased physical capacity, difficulty walking, and increased fall risk. To either prevent or recover from a loss of balance, one must effectively regulate their stepping movements. It is therefore critical to identify how well persons with amputation regulate stepping. Here, we used a multi-objective control framework based on Goal Equivalent Manifolds to identify how persons with transtibial amputation (TTA) regulate lateral stepping while walking without and with lateral perturbations.

RESEARCH QUESTION

When walking in destabilizing environments, do otherwise healthy persons with TTA exhibit greater difficulty regulating lateral stepping due to impaired control? Or do they instead continue to use similar strategies to regulate lateral stepping despite their amputation?

METHODS

Eight persons with unilateral TTA and thirteen able-bodied (AB) controls walked in a virtual environment under three conditions: no perturbations, laterally oscillating visual field, and laterally oscillating treadmill platform. We analyzed step-to-step time series of step widths and absolute lateral body positions. We computed means, standard deviations and Detrended Fluctuation Analysis scaling exponents for each time series and computed how much participants directly corrected step width and position deviations at each step. We compared our results to computational predictions to identify the underlying causes of our experimental findings.

RESULTS

All participants exhibited significantly increased variability, decreased scaling exponents, and tighter direct control when perturbed. Simulations from our stepping regulation models revealed that people responded to the increased variability produced by the imposed perturbations by tightening their control of both step width and lateral position. Participants with TTA exhibited only a few minor differences from AB in lateral stepping regulation, even when subjected to substantially destabilizing lateral perturbations.

SIGNIFICANCE

Since control of stepping is intrinsically multi-objective, developing effective interventions to reduce fall risk in persons with amputation will likely require strategies that adopt multi-objective approaches.

INFLUENCE OF DIABETIC NEUROPATHY ON GAIT COMPLEXITY

ABSTRACT Introduction: Human gait is a complex movement dependent on multilevel neural control, which allows a consistent, regular and complex periodic pattern, properties that characterize it as a nonlinear system. Sensory and motor deficits, with diminished proprioceptive responses, may reduce the adaptive capacity of the system, as demonstrated in Parkinson's, Alzheimer's and Huntington's diseases. However, little is known about the effect of peripheral diabetic neuropathy on these responses. Objectives: To analyze the influence of peripheral diabetic neuropathy on entropy in different gait environments. Methods: Ten elderly patients, with and without a diagnosis of peripheral diabetic neuropathy, walked on a treadmill (initial speed of 3 km/h, with 0.5 km/h increments every 5 minutes up to the speed of 5 km/h) to record center of mass acceleration in the vertical, mediolateral and anteroposterior components throughout the test. The sample entropy of the three vectors was calculated for each test speed. Results: The vertical component did not show any statistically significant differences. The mediolateral component showed statistically significant difference for the factors group, speed, and interaction between factors (group and speed). The anteroposterior component showed statistically significant differences for the group factor, but not for speed and interaction between factors (group and speed). Effect sizes classified as large were found in all the comparisons. Conclusions: Peripheral diabetic neuropathy produced changes in the ability to adapt to changes in the environment during gait, probably due to changes in the complexity of the multilevel neural control system, which depends on motor and sensory feedback, known to be affected by peripheral diabetic neuropathy. Level of Evidence II; Diagnostic studies - Investigating a diagnostic test.

Significance of trends in gait dynamics

Trends in time series generated by physiological control systems are ubiquitous. Determining whether trends arise from intrinsic system dynamics or originate outside of the system is a fundamental problem of fractal series analysis. In the latter case, it is necessary to filter out the trends before attempting to quantify correlations in the noise (residuals). For over two decades, detrended fluctuation analysis (DFA) has been used to calculate scaling exponents of stride time (ST), stride length (SL), and stride speed (SS) of human gait. Herein, rather than relying on the very specific form of detrending characteristic of DFA, we adopt Multivariate Adaptive Regression Splines (MARS) to explicitly determine trends in spatio-temporal gait parameters during treadmill walking. Then, we use the madogram estimator to calculate the scaling exponent of the corresponding MARS residuals. The durations of ST and SL trends are determined to be independent of treadmill speed and have distributions with exponential tails. At all speeds considered, the trends of ST and SL are strongly correlated and are statistically independent of their corresponding residuals. The averages of scaling exponents of ST and SL MARS residuals are slightly smaller than 0.5. Thus, contrary to the interpretation prevalent in the literature, the statistical properties of ST and SL time series originate from the superposition of large scale trends and small scale fluctuations. We show that trends serve as the control manifolds about which ST and SL fluctuate. Moreover, the trend speed, defined as the ratio of instantaneous values of SL and ST trends, is tightly controlled about the treadmill speed. The strong coupling between the ST and SL trends ensures that the concomitant changes of their values correspond to movement along the constant speed goal equivalent manifold as postulated by Dingwell et al. 10.1371/journal.pcbi.1000856.

Load Magnitude and Locomotion Pattern Alter Locomotor System Function in Healthy Young Adult Women

Introduction

During cyclical steady state ambulation, such as walking, variability in stride intervals can indicate the state of the system. In order to define locomotor system function, observed variability in motor patterns, stride regulation and gait complexity must be assessed in the presence of a perturbation. Common perturbations, especially for military populations, are load carriage and an imposed locomotion pattern known as forced marching (FM). We examined the interactive effects of load magnitude and locomotion pattern on motor variability, stride regulation and gait complexity during bipedal ambulation in recruit-aged females.

Methods

Eleven healthy physically active females (18–30 years) completed 1-min trials of running and FM at three load conditions: no additional weight/bodyweight (BW), an additional 25% of BW (BW + 25%), and an additional 45% of BW (BW + 45%). A goal equivalent manifold (GEM) approach was used to assess motor variability yielding relative variability (RV; ratio of “good” to “bad” variability) and detrended fluctuation analysis (DFA) to determine gait complexity on stride length (SL) and stride time (ST) parameters. DFA was also used on GEM outcomes to calculate stride regulation.

Results

There was a main effect of load (p = 0.01) on RV; as load increased, RV decreased. There was a main effect of locomotion (p = 0.01), with FM exhibiting greater RV than running. Strides were regulated more tightly and corrected quicker at BW + 45% compared (p < 0.05) to BW. Stride regulation was greater for FM compared to running. There was a main effect of load for gait complexity (p = 0.002); as load increased gait complexity decreased, likewise FM had less (p = 0.02) gait complexity than running.

Discussion

This study is the first to employ a GEM approach and a complexity analysis to gait tasks under load carriage. Reduction in “good” variability as load increases potentially exposes anatomical structures to repetitive site-specific loading. Furthermore, load carriage magnitudes of BW + 45% potentially destabilize the system making individuals less adaptable to additional perturbations. This is further evidenced by the decrease in gait complexity, which all participants demonstrated values similarly observed in neurologically impaired populations during the BW + 45% load condition.

Detrended fluctuation analysis of gait dynamics when entraining to music and metronomes at different tempi in persons with multiple sclerosis

In persons with multiple sclerosis (PwMS), synchronizing walking to auditory stimuli such as to music and metronomes have been shown to be feasible, and positive clinical effects have been reported on step frequency and perception of fatigue. Yet, the dynamic interaction during the process of synchronization, such as the coupling of the steps to the beat intervals in music and metronomes, and at different tempi remain unknown. Understanding these interactions are clinically relevant, as it reflects the pattern of step intervals over time, known as gait dynamics. 28 PwMS and 29 healthy controls were instructed to walk to music and metronomes at 6 tempi (0–10% in increments of 2%). Detrended fluctuation analysis was applied to calculate the fractal statistical properties of the gait time-series to quantify gait dynamics by the outcome measure alpha. The results showed no group differences, but significantly higher alpha when walking to music compared to metronomes, and when walking to both stimuli at tempi + 8, + 10% compared to lower tempi. These observations suggest that the precision and adaptation gain differ during the coupling of the steps to beats in music compared to metronomes (continuous compared to discrete auditory structures) and at different tempi (different inter-beat-intervals).

On the application of entropic half-life and statistical persistence decay for quantification of time dependency in human gait

Entropic half-life (ENT½) and statistical persistence decay (SPD) was recently introduced as measures of time dependency in stride time intervals during walking. The present study investigated the effect of data length on ENT½ and SPD and additionally applied these measures to stride length and stride speed intervals. First, stride times were collected from subjects during one hour of treadmill walking. ENT½ and SPD were calculated from a range of stride numbers between 250 and 2500. Secondly, stride times, stride lengths and stride speeds were collected from subjects during 16 min of treadmill walking. ENT½ and SPD were calculated from the stride times, stride lengths and stride speeds. The ENT½ values reached a plateau between 1000 and 2500 strides whereas the SPD increased linearly with the number of included strides. This suggests that ENT½ can be compared if 1000 strides or more are included, but only SPD obtained from same number of strides should be compared. The ENT½ and SPD of the stride times were significantly longer compared to that of the stride lengths and stride speeds. This indicates that the time dependency is greater in the motor control of stride time compared to that of stride lengths and stride speeds.

Assessing the Temporal Organization of Walking Variability: A Systematic Review and Consensus Guidelines on Detrended Fluctuation Analysis

Human physiological signals are inherently rhythmic and have a hallmark feature in that even distant intrasignal measurements are related to each other. This relationship is termed long-range correlation and has been recognized as an indicator of the optimal state of the observed physiological systems, among which the locomotor system. Loss of long-range correlations has been found as a result of aging as well as disease, which can be evaluated with detrended fluctuation analysis (DFA). Recently, DFA and the scaling exponent α have been employed for understanding the degeneration of temporal regulation of human walking biorhythms in, for example, Parkinson disease (PD). However, heterogeneous evidence on scaling exponent α values reported in the literature across different population groups has put into question what constitutes a healthy physiological pattern. Therefore, the purpose of this systematic review was to investigate the functional thresholds of scaling exponent α in young vs. older adults, as well as between patients with PD and age-matched asymptomatic controls. Aging and PD exhibited a negative effect size (i.e., led to decreased long-range correlations) of -0.20 and -0.53, respectively. Our meta-analysis based on 14 studies provides evidence that a mean scaling exponent α threshold of 0.86 [2 standard error (0.76, 0.96)] is able to optimally discriminate temporal organization of stride interval between young and old, whereas 0.82 (0.72, 0.92) differentiates patients with PD and age-matched asymptomatic controls. The optimal thresholds presented in this review together with the consensus guidelines for using DFA might allow a more sensitive and reliable application of this metric for understanding human walking physiology than has been achieved to date.

Differences in reproducibility of gait variability and fractal dynamics according to walking duration

BACKGROUND

Gait variability and fractal dynamics may be affected by the walking duration.

OBJECTIVE

The purpose of this study is to examine the reproducibility of stride time while walking on a self-paced treadmill.

METHODS

Fifteen young and healthy subjects walked on the treadmill for 10 minutes. Three to eight minutes duration of the data were used to compare the trial-to-trial and day-to-day reproducibility of the average, variability, and fractal dynamics of stride time.

RESULTS

The results show that all variables had high trial-to-trial reproducibility. In the day-to-day results, the average walking speed and mean stride time showed reproducibility without regard for duration, but the variability and gait fractal dynamics showed differences in reproducibility according to duration. The variability and fractal dynamics showed better reproducibility in less than 5 minutes and over time, respectively. However, both variables generally showed improved reproducibility when average data from two to three rounds were used.

CONCLUSION

Based on the results of this study, it is proposed that variability should be examined using data of 5 min or less, and fractal dynamics should be examined using 5 min or more of repeated data when performing walking tests from a gait dynamics perspective.

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.

Auditory and Visual External Cues Have Different Effects on Spatial but Similar Effects on Temporal Measures of Gait Variability

Walking synchronized to external cues is a common practice in clinical settings. Several research studies showed that this popular gait rehabilitation tool alters gait variability. There is also recent evidence which suggests that alterations in the temporal structure of the external cues could restore gait variability at healthy levels. It is unknown, however, if such alterations produce similar effects if the cueing modalities used are different; visual or auditory. The modality could affect gait variability differentially, since there is evidence that auditory cues mostly act in the temporal domain of gait, while visual cues act in the spatial domain of gait. This study investigated how synchronizing steps with visual and auditory cues that are presented with different temporal structures could affect gait variability during treadmill walking. Three different temporal structured stimuli were used, invariant, fractal and random, in both modalities. Stride times, length and speed were determined, and their fractal scaling (an indicator of complexity) and coefficient of variation (CV) were calculated. No differences were observed in the CV, regardless of the cueing modality and the temporal structure of the stimuli. In terms of the stride time's fractal scaling, we observed that the fractal stimulus induced higher values compared to random and invariant stimuli. The same was also observed in stride length, but only for the visual cueing modality. No differences were observed for stride speed. The selection of the cueing modality seems to be an important feature of gait rehabilitation. Visual cues are possibly a better choice due to the dependency on vision during walking. This is particularly evident during treadmill walking, a common practice in a clinical setting. Because of the treadmill effect on the temporal domain of gait, the use of auditory cues can be minimal, compared to visual cues.

Gait Recognition via Deep Learning of the Center-of-Pressure Trajectory

The fact that every human has a distinctive walking style has prompted a proposal to use gait recognition as an identification criterion. Using end-to-end learning, I investigated whether the center-of-pressure (COP) trajectory is sufficiently unique to identify a person with high certainty. Thirty-six adults walked for 30 min on a treadmill equipped with a force platform that continuously recorded the positions of the COP. The raw two-dimensional signals were sliced into segments of two gait cycles. A set of 20,250 segments from 30 subjects was used to configure and train convolutional neural networks (CNNs). The best CNN classified a separate set containing 2250 segments with an overall accuracy of 99.9%. A second set of 4500 segments from the six remaining subjects was then used for transfer learning. Several small subsamples of this set were selected randomly and used to fine tune the pretrained CNNs. Training with two segments per subject was sufficient to achieve 100% accuracy. The results suggest that every person produces a unique trajectory of underfoot pressures while walking and that CNNs can learn the distinctive features of these trajectories. By applying a pretrained CNN (transfer learning), a couple of strides seem enough to learn and identify new gaits. However, these promising results should be confirmed in a larger sample under realistic conditions.

Flow as an Embodied State. Informed Awareness of Slackline Walking

Flow during exercise has been theorized and studied solely through subjective-retrospective methods as a “scull bound” construct. Recent advances of the radical embodied perspectives on conscious mind and cognition pose challenges to such understanding, particularly because flow during exercise is associated with properties of performer’s movement behavior. In this paper we use the concept of informed awareness to reconceptualize flow experience as a property of the performer-environment coupling, and study it during a slackline walking task. To empirically check the possible relatedness of the behavior-experience complementary pair, two measures were considered. The experiential realm was quantified by the flow short scale and the behavioral realm by the Hurst (H) exponent obtained through accelerometry time series of the legs and the center of body mass (CoM). In order to obtain a coarse-grained insight about the degree of co-varying within the perception-action flow of performers, we conducted correlational and multiple regression analyses. Measures of behavioral variables (H exponents of the dominant, subdominant leg and the CoM, were treated as explanatory, and the flow scale and its subscale (fluency of movements and absorption) scores asresponse variables containing summarized information about perceptual experiences of performers. In order to check for possible mediating or confounding effects of training parameters on the action-perception variables’ covariance, we included two additional variables which measured the degree of engagement of participants with the task. Results revealed that the temporal structure of fluctuations of the dominant leg, as measured by the Hurst exponent, was a strong mediator of effects of training variables and the subdominant leg fluctuations, on the flow scale and the subscale scores. The magnitude of Hurst exponents of both legs was informative about the degree of stability within the performer-environment system. The degree of critical slowing down, as measured by Hurst exponents, consistently co-varied with the flow scale and subscales. The experience of flow during the slackline walking task was dominantly saturated by the perceived fluency of movements and less so by the absorption experience. The stable co-variance of perception-action variables signified the embodied nature of the flow experience.

Multisensory integration and behavioral stability

Information coming from multiple senses, as compared to a single one, typically enhances our performance. The multisensory improvement has been extensively examined in perception studies, as well as in tasks involving a motor response like a simple reaction time. However, how this effect extends to more complex behavior, typically involving the coordination of movements, such as bimanual coordination or walking, is still unclear. A critical element in achieving motor coordination in complex behavior is its stability. Reaching a stable state in the coordination pattern allows to sustain complex behavior over time (e.g., without interruption or negative consequences, like falling). This study focuses on the relation between stability in the coordination of movement patterns, like walking, and multisensory improvement. Participants walk with unimodal and audio-tactile metronomes presented either at their preferred rate or at a slower walking rate, the instruction being to synchronize their steps to the metronomes. Walking at a slower rate makes gait more variable than walking at the preferred rate. Interestingly however, the multimodal stimuli enhance the stability of motor coordination but only in the slower condition. Thus, the reduced stability of the coordination pattern (at a slower gait rate) prompts the sensorimotor system to capitalize on multimodal stimulation. These findings provide evidence of a new link between multisensory improvement and behavioral stability, in the context of ecological sensorimotor task.

Bodywide fluctuations support manual exploration: Fractal fluctuations in posture predict perception of heaviness and length via effortful touch by the hand

The human haptic perceptual system respects a bodywide organization that responds to local stimulation through full-bodied coordination of nested tensions and compressions across multiple nonoverlapping scales. Under such an organization, the suprapostural task of manually hefting objects to perceive their heaviness and length should depend on roots extending into the postural control for maintaining upright balance on the ground surface. Postural sway of the whole body should thus carry signatures predicting what the hand can extract by hefting an object. We found that fractal fluctuations in Euclidean displacement in the participants' center of pressure (CoP) contributed to perceptual judgments by moderating how the participants' hand picked up the informational variable of the moment of inertia. The role of fractality in CoP displacement in supporting heaviness and length judgments increased across trials, indicating that the participants progressively implicate their fractal scaling in their perception of heaviness and length. Traditionally, we had to measure fractality in hand movements to predict perceptual judgments by manual hefting. However, our findings suggest that we can observe what is happening at hand in the relatively distant-from-hand measure of CoP. Our findings reveal the complex relationship through which posture supports manual exploration, entailing perception of the intended properties of hefted objects (heaviness or length) putatively through the redistribution of forces throughout the body.

Fractal properties and short-term correlations in motor control in cycling: influence of a cognitive challenge

Fluctuations in cyclic tasks periods is a known characteristic of human motor control. Specifically, long-range fractal fluctuations have been evidenced in the temporal structure of these variations in human locomotion and thought to be the outcome of a multicomponent physiologic system in which control is distributed across intricate cortical, spinal and neuromuscular regulation loops. Combined with long-range correlation analyses, short-range autocorrelations have proven their use to describe control distribution across central and motor components. We used relevant tools to characterize long- and short-range correlations in revolution time series during cycling on an ergometer in 19 healthy young adults. We evaluated the impact of introducing a cognitive task (PASAT) to assess the role of central structures in control organization. Autocorrelation function and detrending fluctuation analysis (DFA) demonstrated the presence of fractal scaling. PSD in the short range revealed a singular behavior which cannot be explained by the usual models of even-based and emergent timing. The main outcomes are that (1) timing in cycling is a fractal process, (2) this long-range fractal behavior increases in persistence with dual-task condition, which has not been previously observed, (3) short-range behavior is highly persistent and unaffected by dual-task. Relying on the inertia of the oscillator may be a way to distribute more control to the periphery, thereby allocating less resources to central process and better managing additional cognitive demands. This original behavior in cycling may explain the high short-range persistence unaffected by dual-task, and the increase in long-range persistence with dual-task.

Complexity of human walking: the attractor complexity index is sensitive to gait synchronization with visual and auditory cues

Background

During steady walking, gait parameters fluctuate from one stride to another with complex fractal patterns and long-range statistical persistence. When a metronome is used to pace the gait (sensorimotor synchronization), long-range persistence is replaced by stochastic oscillations (anti-persistence). Fractal patterns present in gait fluctuations are most often analyzed using detrended fluctuation analysis (DFA). This method requires the use of a discrete times series, such as intervals between consecutive heel strikes, as an input. Recently, a new nonlinear method, the attractor complexity index (ACI), has been shown to respond to complexity changes like DFA, while being computed from continuous signals without preliminary discretization. Its use would facilitate complexity analysis from a larger variety of gait measures, such as body accelerations. The aim of this study was to further compare DFA and ACI in a treadmill experiment that induced complexity changes through sensorimotor synchronization.

Methods

Thirty-six healthy adults walked 30 min on an instrumented treadmill under three conditions: no cueing, auditory cueing (metronome walking), and visual cueing (stepping stones). The center-of-pressure trajectory was discretized into time series of gait parameters, after which a complexity index (scaling exponent alpha) was computed via DFA. Continuous pressure position signals were used to compute the ACI. Correlations between ACI and DFA were then analyzed. The predictive ability of DFA and ACI to differentiate between cueing and no-cueing conditions was assessed using regularized logistic regressions and areas under the receiver operating characteristic curves (AUC).

Results

DFA and ACI were both significantly different among the cueing conditions. DFA and ACI were correlated (Pearson’s r = 0.86). Logistic regressions showed that DFA and ACI could differentiate between cueing/no cueing conditions with a high degree of confidence (AUC = 1.00 and 0.97, respectively).

Conclusion

Both DFA and ACI responded similarly to changes in cueing conditions and had comparable predictive power. This support the assumption that ACI could be used instead of DFA to assess the long-range complexity of continuous gait signals. However, future studies are needed to investigate the theoretical relationship between DFA and ACI.

Years of running experience influences stride-to-stride fluctuations and adaptive response during step frequency perturbations in healthy distance runners

RESEARCH QUESTION

The current study investigated stride-to-stride fluctuations of step rate and contact time in response to enforced step frequency perturbations as well as adaptation and de-adaptation behavior.

METHODS

Forty distance runners ran at a self-selected speed and were asked to match five different enforced step frequencies (150, 160, 170, 180, and 190 beats per min). The influence of experience was explored, because running is a skill that presumably gets better with practice, and increased years of running experience is protective against injury. Detrended fluctuation analysis was used to determine the strength of long-range correlations in gait fluctuations at baseline, during the perturbation, and post-perturbation. Adaptive response was measured by the ability to match, rate of matching, and aftereffect of step frequency perturbations.

RESULTS

The structure of stride-to-stride fluctuations for step rate and contact time did not change during the perturbation or post-perturbation compared to baseline. However, fluctuations in step rate were affected by the level of perturbation. Runners with the most experience had a less persistent structural gait pattern for both step rate and contact time at baseline. Highly experienced runners also demonstrated the best adaptive response. They better matched the enforced step frequency, reached the enforced step frequency sooner, and returned to preferred step frequency more quickly following removal of the perturbation.

SIGNIFICANCE

These findings indicate baseline locomotor flexibility may be beneficial to achieve task demands and return to a stable state once the task is complete. Increased locomotor flexibility may also be a contributing factor for reduced injury risk in experienced runners.

Synchronization dynamics modulates stride-to-stride fluctuations when walking to an invariant but not to a fractal-like stimulus

Walking with different types of cueing/stimulus (i.e. auditory, visual) has been shown to alter gait variability, thus emerging as an innovative therapeutical tool to restore abnormal gait variability in clinical populations. However, the majority of the research in this area has focused on auditory stimuli while visual stimuli are an understudied alternative that needs more attention, particularly due to the natural dependence on vision during walking. Furthermore, the time differences between the occurrences of the walking steps and the sensory cues, also known as asynchronies, have also received minimal attention, even though the ability to synchronize with different stimuli is of great importance. This study investigated how synchronizing to visual stimuli with different temporal structures could affect gait variability and the respective asynchronies. Participants performed four 15-min walking trials around an indoor track while wearing insole footswitches for the following conditions: a) self-paced walking, and b) walking with glasses that instructed the subjects to step in sync with a virtual moving bar. The stepping occurences of the moving bar were presented in three different ways b1) non-variable, b2) variable and b3) random. Stride times and asynchronies were determined, and the mean values along with the fractal scaling (an indicator of the complexity) in their time series, were calculated. The fractal scaling of the stride times was unaltered when participants walked with the variable stimulus as compared to the self-paced walking condition; while fractal scaling was significantly decreased during the non-variable and random conditions, indicating a loss of complexity for these two conditions. No differences were observed in the means or the fractal scaling of the asynchronies. The correlation analysis between stride times and asynchronies revealed a strong relationship for the non-variable condition but a weak relationship for both variable and random conditions. Taken together, the present study results supports the idea of an existing internal timekeeper that exhibits complexity. We have shown that this complex pattern is similar regardless of the stimulus condition, suggesting that the system's complexity is likely to be expressed at the task performance level - asyncrhonies - when walking to a stimulus. Thus, future research in sensoriomotor gait synchronization should focus and further explore the role of the asynchronies, as it may be of clinical significance.

Tightening Up the Control of Treadmill Walking: Effects of Maneuverability Range and Acoustic Pacing on Stride-to-Stride Fluctuations

The correlational structure of stride-to-stride fluctuations differs between healthy and pathological gait. Uncorrelated and anti-persistent stride-to-stride fluctuations are believed to indicate pathology whereas persistence represents healthy functioning. However, this reading can be questioned because the correlational structure changes with task constraints, like acoustic pacing, signifying the tightness of control over particular gait parameters. We tested this "tightness-of-control interpretation" by varying the maneuverability range during treadmill walking (small, intermediate, and large walking areas), with and without acoustic pacing. Stride-speed fluctuations exhibited anti-persistence, suggesting that stride speeds were tightly controlled, with a stronger degree of anti-persistence for smaller walking areas. Constant-speed goal-equivalent-manifold decompositions revealed simultaneous control of stride times and stride lengths, especially for smaller walking areas to limit stride-speed fluctuations. With acoustic pacing, participants followed both constant-speed and constant-stride-time task goals. This was reflected by a strong degree of anti-persistence around the stride-time by stride-length point that uniquely satisfied both goals. Our results strongly support the notion that anti-persistence in stride-to-stride fluctuations reflect the tightness of control over the associated gait parameter, while not tightly regulated gait parameters exhibit statistical persistence. We extend the existing body of knowledge by showing quantitative changes in anti-persistence of already tightly regulated stride-speed fluctuations.

Dual Mode Gait Sonification for Rehabilitation After Unilateral Hip Arthroplasty

The pattern of gait after hip arthroplasty strongly affects regeneration and quality of life. Acoustic feedback could be a supportive method for patients to improve their walking ability and to regain a symmetric and steady gait. In this study, a new gait sonification method with two different modes—real-time feedback (RTF) and instructive model sequences (IMS)—is presented. The impact of the method on gait symmetry and steadiness of 20 hip arthroplasty patients was investigated. Patients were either assigned to a sonification group (SG) (n = 10) or a control group (CG) (n = 10). All of them performed 10 gait training sessions (TS) lasting 20 min, in which kinematic data were measured using an inertial sensor system. Results demonstrate converging step lengths of the affected and unaffected leg over time in SG compared with a nearly parallel development of both legs in CG. Within the SG, a higher variability of stride length and stride time was found during the RTF training mode in comparison to the IMS mode. Therefore, the presented dual mode method provides the potential to support gait rehabilitation as well as home-based gait training of orthopedic patients with various restrictions.

Humans use multi-objective control to regulate lateral foot placement when walking

A fundamental question in human motor neuroscience is to determine how the nervous system generates goal-directed movements despite inherent physiological noise and redundancy. Walking exhibits considerable variability and equifinality of task solutions. Existing models of bipedal walking do not yet achieve both continuous dynamic balance control and the equifinality of foot placement humans exhibit. Appropriate computational models are critical to disambiguate the numerous possibilities of how to regulate stepping movements to achieve different walking goals. Here, we extend a theoretical and computational Goal Equivalent Manifold (GEM) framework to generate predictive models, each posing a different experimentally testable hypothesis. These models regulate stepping movements to achieve any of three hypothesized goals, either alone or in combination: maintain lateral position, maintain lateral speed or “heading”, and/or maintain step width. We compared model predictions against human experimental data. Uni-objective control models demonstrated clear redundancy between stepping variables, but could not replicate human stepping dynamics. Most multi-objective control models that balanced maintaining two of the three hypothesized goals also failed to replicate human stepping dynamics. However, multi-objective models that strongly prioritized regulating step width over lateral position did successfully replicate all of the relevant step-to-step dynamics observed in humans. Independent analyses confirmed this control was consistent with linear error correction and replicated step-to-step dynamics of individual foot placements. Thus, the regulation of lateral stepping movements is inherently multi-objective and balances task-specific trade-offs between competing task goals. To determine how people walk in their environment requires understanding both walking biomechanics and how the nervous system regulates movements from step-to-step. Analogous to mechanical “templates” of locomotor biomechanics, our models serve as “control templates” for how humans regulate stepping movements from each step to the next. These control templates are symbiotic with well-established mechanical templates, providing complimentary insights into walking regulation.

When we walk, we walk in real-world contexts and with specific goal to achieve. Side-to-side movements are paramount because walking bipeds (humans, animals, robots, etc.) are inherently more unstable laterally. This is particularly important in older adults as sideways falls greatly increase hip fracture risk. Additionally, we normally walk on paths that limit (more or less) our lateral movements. Appropriately regulating lateral stepping movements is thus critical to achieving successful locomotion in any such context. Here, we use appropriate models to test competing hypotheses about how humans regulate lateral stepping movements from each step to the next to identify what task goals they try to achieve. Our work both bridges and unifies perspectives from dynamic walking and computational motor control to provide a coherent theoretical and computational framework from which to study motor regulation in the context of goal-directedness across a wide range of walking tasks and/or conditions.

Lower limb joint angle variability and dimensionality are different in stairmill climbing and treadmill walking

The present study tested if the quadratic relationship which exists between stepping frequency and gait dynamics in walking can be generalized to stairmill climbing. To accomplish this, we investigated the joint angle dynamics and variability during continuous stairmill climbing at stepping frequencies both above and below the preferred stepping frequency (PSF). Nine subjects performed stairmill climbing at 80, 90, 100, 110 and 120% PSF and treadmill walking at preferred walking speed during which sagittal hip, knee and ankle angles were extracted. Joint angle dynamics were quantified by the largest Lyapunov exponent (LyE) and correlation dimension (CoD). Joint angle variability was estimated by the mean ensemble standard deviation (meanSD). MeanSD and CoD for all joints were significantly higher during stairmill climbing but there were no task differences in LyE. Changes in stepping frequency had only limited effect on joint angle variability and did not affect joint angle dynamics. Thus, we concluded that the quadratic relationship between stepping frequency and gait dynamics observed in walking is not present in stairmill climbing based on the investigated parameters.

Multifractality of Unperturbed and Asymmetric Locomotion

The purpose of this study was to explore the extent of multifractality in unperturbed and constrained locomotion, and to determine if multifractality predicted gait adaptability. Young, healthy participants (n = 15) walked at preferred and slow speeds, as well as asymmetrically (one leg at half speed) on a split-belt treadmill. Stride time multifractality was assessed via local detrended fluctuation analysis, which evaluates the evolution of fluctuations both spatially and temporally. Unperturbed walking exhibited monofractal behavior. Asymmetric walking displayed greater multifractality in the faster moving limb, indicating more intermittent periods of extreme high or low variance. Multifractality was not associated with adaptation to asymmetric walking. These findings further suggest that unperturbed locomotion is monofractal and establish that perturbed walking yields multifractal behavior.

Entrainment and Synchronization to Auditory Stimuli During Walking in Healthy and Neurological Populations: A Methodological Systematic Review

Background: Interdisciplinary work is needed for scientific progress, and with this review, our interest is in the scientific progress toward understanding the underlying mechanisms of auditory-motor coupling, and how this can be applied to gait rehabilitation. Specifically we look into the process of entrainment and synchronization; where entrainment is the process that governs the dynamic alignments of the auditory and motor domains based on error-prediction correction, whereas synchronization is the stable maintenance of timing during auditory-motor alignment. Methodology: A systematic literature search in databases PubMed and Web of Science were searched up to 9th of August 2017. The selection criteria for the included studies were adult populations, with a minimum of five participants, investigating walking to an auditory stimulus, with an outcome measure of entrainment, and synchronization. The review was registered in PROSPERO as CRD42017080325. Objectives: The objective of the review is to systematically describe the metrics which measure entrainment and synchronization to auditory stimuli during walking in healthy and neurological populations. Results: Sixteen articles were included. Fifty percent of the included articles had healthy controls as participants (N = 167), 19% had neurological diseases such as Huntington's and Stroke (N = 76), and 31% included both healthy and neurological [Parkinson's disease (PD) and Stroke] participants (N = 101). In the included studies, six parameters were found to capture the interaction between the human movement and the auditory stimuli, these were: cadence, relative phase angle, resultant vector length, interval between the beat and the foot contact, period matching performance, and detrended fluctuation analysis. Conclusion: In this systematic review, several metrics have been identified, which measure the timing aspect of auditory-motor coupling and synchronization of auditory stimuli in healthy and neurological populations during walking. The application of these metrics may enhance the current state of the art and practice across the neurological gait rehabilitation. These metrics also have current shortcomings. Of particular pertinence is our recommendation to consider variability in data from a time-series rather than time-windowed viewpoint. We need it in view of the promising practical applications from which the studied populations may highly benefit in view of personalized medical care.

Humans control stride-to-stride stepping movements differently for walking and running, independent of speed

As humans walk or run, external (environmental) and internal (physiological) disturbances induce variability. How humans regulate this variability from stride-to-stride can be critical to maintaining balance. One cannot infer what is "controlled" based on analyses of variability alone. Assessing control requires quantifying how deviations are corrected across consecutive movements. Here, we assessed walking and running, each at two speeds. We hypothesized differences in speed would drive changes in variability, while adopting different gaits would drive changes in how people regulated stepping. Ten healthy adults walked/ran on a treadmill under four conditions: walk or run at comfortable speed, and walk or run at their predicted walk-to-run transition speed. Time series of relevant stride parameters were analyzed to quantify variability and stride-to-stride error-correction dynamics within a Goal-Equivalent Manifold (GEM) framework. In all conditions, participants' stride-to-stride control respected a constant-speed GEM strategy. At each consecutively faster speed, variability tangent to the GEM increased (p ≤ 0.031), while variability perpendicular to the GEM decreased (p ≤ 0.044). There were no differences (p ≥ 0.999) between gaits at the transition speed. Differences in speed determined how stepping variability was structured, independent of gait, confirming our first hypothesis. For running versus walking, measures of GEM-relevant statistical persistence were significantly less (p ≤ 0.004), but showed minimal-to-no speed differences (0.069 ≤ p ≤ 0.718). When running, people corrected deviations both more quickly and more directly, each indicating tighter control. Thus, differences in gait determined how stride-to-stride fluctuations were regulated, independent of speed, confirming our second hypothesis.

Performance of an attention-demanding task during treadmill walking shifts the noise qualities of step-to-step variation in step width

BACKGROUND

The fractal scaling evident in the step-to-step fluctuations of stepping-related time series reflects, to some degree, neuromotor noise.

RESEARCH QUESTION

The primary purpose of this study was to determine the extent to which the fractal scaling of step width, step width and step width variability are affected by performance of an attention-demanding task. We hypothesized that the attention-demanding task would shift the structure of the step width time series toward white, uncorrelated noise.

METHODS

Subjects performed two 10-min treadmill walking trials, a control trial of undisturbed walking and a trial during which they performed a mental arithmetic/texting task. Motion capture data was converted to step width time series, the fractal scaling of which were determined from their power spectra.

RESULTS

Fractal scaling decreased by 22% during the texting condition (p < 0.001) supporting the hypothesized shift toward white uncorrelated noise. Step width and step width variability increased 19% and five percent, respectively (p < 0.001). However, a stepwise discriminant analysis to which all three variables were input revealed that the control and dual task conditions were discriminated only by step width fractal scaling.

SIGNIFICANCE

The change of the fractal scaling of step width is consistent with increased cognitive demand and suggests a transition in the characteristics of the signal noise. This may reflect an important advance toward the understanding of the manner in which neuromotor noise contributes to some types of falls. However, further investigation of the repeatability of the results, the sensitivity of the results to progressive increases in cognitive load imposed by attention-demanding tasks, and the extent to which the results can be generalized to the gait of older adults seems warranted.

Frequency-Specific Fractal Analysis of Postural Control Accounts for Control Strategies

Diverse indicators of postural control in Humans have been explored for decades, mostly based on the trajectory of the center-of-pressure. Classical approaches focus on variability, based on the notion that if a posture is too variable, the subject is not stable. Going deeper, an improved understanding of underlying physiology has been gained from studying variability in different frequency ranges, pointing to specific short-loops (proprioception), and long-loops (visuo-vestibular) in neural control. More recently, fractal analyses have proliferated and become useful additional metrics of postural control. They allowed identifying two scaling phenomena, respectively in short and long timescales. Here, we show that one of the most widely used methods for fractal analysis, Detrended Fluctuation Analysis, could be enhanced to account for scalings on specific frequency ranges. By computing and filtering a bank of synthetic fractal signals, we established how scaling analysis can be focused on specific frequency components. We called the obtained method Frequency-specific Fractal Analysis (FsFA) and used it to associate the two scaling phenomena of postural control to proprioceptive-based control loop and visuo-vestibular based control loop. After that, convincing arguments of method validity came from an application on the study of unaltered vs. altered postural control in athletes. Overall, the analysis suggests that at least two timescales contribute to postural control: a velocity-based control in short timescales relying on proprioceptive sensors, and a position-based control in longer timescales with visuo-vestibular sensors, which is a brand-new vision of postural control. Frequency-specific scaling exponents are promising markers of control strategies in Humans.

Effects of manipulated auditory information on local dynamic gait stability

Auditory information affects sensorimotor control of gait. Noise or active noise cancelling alters the perception of movement related sounds and, probably, gait stability. The aim of the current study was to evaluate the effects of noise cancelling on gait stability. Twenty-five healthy older subjects (70 ± 6 years) were included into a randomized cross-over study. Gait stability (largest Lyapunov exponent) in normal overground walking was determined for the following hearing conditions: no manipulation and active noise cancelling. To assess differences between the two hearing conditions (no manipulation vs. active noise cancelling), Student's repeated measures t-test was used. The results indicate an improvement of gait stability when using active noise cancelling compared to normal hearing. In conclusion, our results indicate that auditory information might not be needed for a stable gait in elderly.