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

Smartphone usage during walking decreases the positive persistency in gait cycle variability

Gait cycle variability during steady walking, described by the stride interval time series, has been used as a gait-stability-related measure. In particular, the positive persistency in the stride intervals with 1/f-like fluctuation and reduction of the persistency are the well-documented metrics that can characterize gait patterns of healthy young adults and elderly including patients with neurological diseases, respectively. Here, we examined effects of a dual task on gait cycle variability in healthy young adults, based on the mean and standard deviation statistics as well as the positive persistency of the stride intervals during steady walking on a treadmill. Specifically, three gait conditions were examined: control condition, non-cognitive task with holding a smartphone in front of the chest using their dominant hand and looking fixedly at a blank screen of the smartphone, and cognitive motor task with holding a smartphone as in the non-cognitive task and playing a puzzle game displayed on the smartphone by one-thumb operation. We showed that only the positive persistency, not the mean and standard deviation statistics, was affected by the cognitive and motor load of smartphone usage in the cognitive condition. More specifically, the positive persistency exhibited in the control and the non-cognitive conditions was significantly reduced in the cognitive condition. Our results suggest that the decrease in the positive persistency during the cognitive task, which might represent the deterioration of healthy gait pattern, is caused endogenously by the cognitive and motor load, not necessarily by the reduction of visual field as often hypothesized.

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.

Trunk variability and local dynamic stability during gait after generalized fatigue induced by incremental exercise test in young women in different phases of the menstrual cycle

Purpose

The purpose of this study was to identify how generalized fatigue along with hormonal changes throughout the menstrual cycle affects trunk variability and local dynamic stability during gait.

Methods

General fatigue was induced by an incremental test on a treadmill, and the menstrual cycle was divided into three phases: follicular, ovulatory, and luteal. Twenty-six healthy, young volunteers (aged 18 to 28 years) who did not use oral contraceptives or other hormonal drugs with a regular menstrual cycle participated in the study. They walked on the treadmill for 4 min at the preferred speed, before the incremental test, followed by four sets of 4 min alternating between walking, also at preferred speed, and resting. From trunk kinematic data, the following were extracted: the mean of the standard deviation along strides, as a measure of variability, and the maximum Lyapunov exponent, as a measure of local dynamic stability (LDS).

Results

After the incremental test, variability increased, and LDS decreased. However, they showed a tendency to return to the initial value faster in women compared to previous results for men. In the follicular phase, which has less hormonal release, the volunteers had an almost complete recovery in LDS soon after the first rest interval, suggesting that female hormones can interfere with fatigue recovery. Nevertheless, concerning the LDS, it was significantly lower in the luteal phase than in the follicular phase.

Conclusion

Women that are not taking oral contraceptives should be aware that they are susceptible to increased gait instabilities in the pre-menstrual phase after strenuous activities.

Restoring walking ability in older adults with arm-in-arm gait training: study protocol for the AAGaTT randomized controlled trial

CONTEXT

Falls are a significant problem among older adults. While balance and functional exercises have been shown to be effective, it remains unclear whether regular walking has specific effects on reducing the risk of falls.

RATIONALE

Older people who fall frequently have impaired gait patterns. Recent studies have suggested using interpersonal synchronization: while walking arm-in-arm, an older person synchronizes steps with a younger person to reinstate a better gait pattern. This method of gait training may reduce the risk of falls.

OBJECTIVE

The aim is to assess the efficacy of an arm-in-arm gait-training program in older people.

DESIGN

The arm-in-arm gait training trial (AAGaTT) is a single-site, open label, two-arm, randomized controlled trial.

PARTICIPANTS

We will enroll 66 dyads of older people and their younger "gait instructors". The older participants must be > 70 years old with adequate walking ability. They must have experienced a fall in the year prior to study entry.

INTERVENTION

Dyads will walk an indoor course for 30 min either side-by-side without contact (control group) or arm-in-arm while synchronizing their gait (intervention group). The gait training will be repeated three times a week for four weeks.

OUTCOMES

The main outcome will be the walking speed measured in five-minute walking trials performed at baseline and at the end of each intervention week (week 1 - week 4), and at week 7. Gait quality will be assessed using accelerometers. We will also assess perceived physical activity and health using questionnaires. Finally, we will monitor fall incidence over 18 months. We will evaluate whether outcomes are more improved in the intervention group compared to the control group. In addition, interviews will be conducted to assess the perception of the gait training.

EXPECTED RESULTS

Recent advances in the neurophysiology of motor control have shown that synchronizing gait to external cues or to a human partner can increase the efficiency of gait training. The expected benefits of arm-in-arm gait training are: reduced risk of falls, safe treatment with no adverse effects, and high adherence. This gait training program could be a low-cost intervention with positive effects on the health and well-being of seniors.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05627453. Date of registration: 11.25.2022.

Is Lyapunov exponent a reliable metric to detect dynamic stability in Parkinson's disease?

Idiopathic Parkinson's disease (PD) is the second most common neurodegenerative disorder worldwide. It affects the nervous system, causing motor and non-motor symptomatology. However, its clinical diagnosis remains dependent on the expertise of clinicians, as perceptual clinical scales are often used. Gait stability is one of the most relevant motor signs in PD. Nonetheless, it is usually not reported or quantified, possibly due to its unclear meaning and the high variability of metrics used in the literature. This work aims to identify a reliable and objective indicator that clinicians can use to assess patients in realistic contexts. We focused on the Largest Lyapunov Exponent (LLE), being the most common metric used in previous research works to quantify gait stability. The short and long-term LLEs were calculated in a group of 34 healthy and 42 participants diagnosed with PD. The long-term LLE extracted from the chest, right arm and right foot sensors showed statistical differences between subjects with PD and healthy control (HC) subjects, showing that the HC subjects are more stable than PD patients, whereas the short-term LLE showed the opposite results. Further investigation is required to clarify the reliability of this metric to detect and rate gait stability in people affected with PD.Clinical Relevance- This study is the first step towards the identification of an objective methodology to assess gait stability in clinical settings. Achieving this goal will contribute to improve the understanding and support the diagnosis of gait disorders that cause gait stability problems.

Adapting Footfall Rhythmicity to Auditory Perturbations Affects Resilience of Locomotor Behavior: A Proof-of-Concept Study

For humans, the ability to effectively adapt footfall rhythm to perturbations is critical for stable locomotion. However, only limited information exists regarding how dynamic stability changes when individuals modify their footfall rhythm. In this study, we recorded 3D kinematic activity from 20 participants (13 males, 18–30 years old) during walking on a treadmill while synchronizing with an auditory metronome sequence individualized to their baseline walking characteristics. The sequence then included unexpected temporal perturbations in the beat intervals with the subjects required to adapt their footfall rhythm accordingly. Building on a novel approach to quantify resilience of locomotor behavior, this study found that, in response to auditory perturbation, the mean center of mass (COM) recovery time across all participants who showed deviation from steady state (N = 15) was 7.4 (8.9) s. Importantly, recovery of footfall synchronization with the metronome beats after perturbation was achieved prior (+3.4 [95.0% CI +0.1, +9.5] s) to the recovery of COM kinematics. These results highlight the scale of temporal adaptation to perturbations and provide implications for understanding regulation of rhythm and balance. Thus, our study extends the sensorimotor synchronization paradigm to include analysis of COM recovery time toward improving our understanding of an individual’s resilience to perturbations and potentially also their fall risk.

Evaluating dynamic similarity of fixed, self-selected and anatomically scaled speeds in non-linear analysis of gait during treadmill running

OBJECTIVES

The aim of this study is to evaluate how speed affects non-linear measures of variability. Fixed and self-selected speeds were compared to an anatomically scaled speed calculated based on leg length to evaluate which provided a more reproducible result between subjects.

METHODS

Sixteen subjects ran on a treadmill at a fixed, scaled and self-selected speed and at ±10% in each case. Kinematic data were collected for two minutes at 250 Hz for each trial. Sample entropy (SaEn) and maximum Lyapunov exponents (LyE) were calculated from the sagittal knee and hip joint angles to evaluate regularity of gait and local stability. These nonlinear measures were compared to evaluate the dynamic similarity of the movement in each case, and to evaluate speed as a confounding variable in non-linear analysis.

RESULTS

An anatomically scaled speed shows more dynamic similarity than a fixed or self-selected speed with the lowest observed coefficient of variation for each measure. This was found to be statistically significant for both nonlinear measures of the hip (SaEn p = 0.038; LyE p = 0.040). Speed was not found to be a confounding variable in non-linear analysis of running gait of a healthy population (η² < 0.05).

CONCLUSIONS

Changes in speed by ±10% do not significantly affect stability and variability of gait for healthy participants, suggesting that they make adaptations to ensure optimal gait variability. Anatomically scaled speeds provide a more reliable methodology for both linear and non-linear analysis by providing a definitive protocol, suggesting it could replace self-selected or fixed speeds in future research.

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).

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.

Effects of triceps surae fatigue and weight training level on gait variability and local stability in young adults

Muscle fatigue negatively affects gait, and the changes in gait pattern due to muscle fatigue is influenced by which muscles are fatigued and pre-existing physical activity levels. However, how these factors alter gait stability and variability, measures related to risk of fall, remains unclear. To explore how muscular fatigue affects linear and nonlinear gait features in young adults, the effects of triceps surae fatigue and weight training level on gait variability and local stability, as well as a 12-min recovery time of post-fatigue period, were evaluated in young adults (trained and untrained groups). Some features were estimated, i.e., (i) step length (SL) and step frequency (SF), (ii) average standard deviation of trunk acceleration along strides (VAR), and (iii) local dynamic stability (LDS; maximum Lyapunov exponent). LDS presented a significant increase in the anterior-posterior direction with recovery to trained group. SL and SF changed immediately post-fatigue and recovered for both groups, while VAR increased significantly in all directions, with a recovery in the vertical direction for both groups and in the medial-lateral direction for trained group. Localized fatigue affected the analyzed gait variables independent of the participant's training condition, and an interval of 12 min does not seem to be enough for a complete recovery, suggesting a longer recovery period after tasks involving localized triceps surae fatigue to guarantee basal levels of gait variability and local stability. Graphical abstract Flow chart of the experimental protocol. A) Pre-fatigue: 4 min walking at PWS. B) Post-fatigue: first 4 min walking after fatigue protocol. C) Post-fatigue: second 4 min walking after fatigue protocol. D) Post-fatigue: third 4 min walking after fatigue protocol (PWS, preferred walking speed; AP, anterior-posterior; V, vertical; ML, medial-lateral).

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.

Head motion predictability explains activity-dependent suppression of vestibular balance control

Vestibular balance control is dynamically weighted during locomotion. This might result from a selective suppression of vestibular inputs in favor of a feed-forward balance regulation based on locomotor efference copies. The feasibility of such a feed-forward mechanism should however critically depend on the predictability of head movements (HMP) during locomotion. To test this, we studied in 10 healthy subjects the differential impact of a stochastic vestibular stimulation (SVS) on body sway (center-of-pressure, COP) during standing and walking at different speeds and compared it to activity-dependent changes in HMP. SVS-COP coupling was determined by correlation analysis in frequency and time domains. HMP was quantified as the proportion of head motion variance that can be explained by the average head trajectory across the locomotor cycle. SVS-COP coupling decreased from standing to walking and further dropped with faster locomotion. Correspondingly, HMP increased with faster locomotion. Furthermore, SVS-COP coupling depended on the gait-cycle-phase with peaks corresponding to periods of least HMP. These findings support the assumption that during stereotyped human self-motion, locomotor efference copies selectively replace vestibular cues, similar to what was previously observed in animal models.

Rhythm-Motor Dual Task Intervention for Fall Prevention in Healthy Older Adults

This study aimed to investigate the effects of a rhythm-motor dual task intervention on cognitive and gait control for older adults in relation to fall prevention. Ten healthy older adults participated in a rhythm-motor dual task intervention and 10 participated in the control group. The intervention group received 16 30-min intervention sessions for 8 weeks. During the intervention sessions, participants engaged in walking or bimanual tapping as a primary motor task with concurrent rhythm tasks including playing instruments and rhythmic chanting or singing. At pretest and post-test, measures of cognition, balance/mobility, and gait were administered. A significant difference between groups was found for part B of the Trail Making Test (TMT-B) measure that involved executive control of attention. Also, changes in the gait ratio in the dual task condition of walking while playing an instrument were significantly different between groups. The findings in this study support the use of the rhythm-motor dual task intervention for increasing available cognitive resources and improving gait control, which are critical factors in fall prevention.

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.

Comparison of selected measures of gait stability derived from center of pressure displacement signal during single and dual-task treadmill walking

Steady state gait dynamics has been examined using the measures of regularity, local dynamic stability, and variability. This study investigates the relationship between these measures under increasing cognitive loads. Participants walked on an instrumented treadmill at 1 m/s under walk only and two dual-task conditions. The secondary tasks were visuomotor cognitive games (VCG) of increasing difficulty level. The center of pressure displacement in the mediolateral direction (ML COP-D) and cognitive game performance were recorded for analysis. The following measures were calculated: (1) sample entropy (SampEn) and quantized dynamical entropy (QDE) of the ML COP-D, (2) short-term largest Lyapunov exponent (LLE) of the ML COP-D, and (3) variability of inter-stride spatio-temporal gait variables. Entropy and variability measures significantly increased from walk only to both dual-task conditions. Whereas, the short-term LLE increased only during the easy VCG task. No measure was sensitive to the difficulty level of the VCG tasks. The variability of heel strike positions in the mediolateral direction was positively correlated with SampEn and QDE. However, there were no significant correlations between the short-term LLE and either variability measures or entropy measures. These findings confirm that each of these measures is representative of a different aspect of human gait dynamics.

The complexity of human performance variability on watch standing task

The primary objective of this study was to examine the complexity of human temporal variability of topside roving watch task in naval operations concerning the reported times of ship status and to explore the potential presence of chaotic behavior and fractal properties of the reported log times. Topside rover reporting time intervals recorded in the deck logs of the USS Jason Dunham over the 2013-2015 period were analyzed to understand the underlying complexity of the watch standing task that is critical to the success of naval operations. The results on the 0-1 test, analysis of the largest Lyapunov exponents, as well the exploration of the fractal dimension and 1/f spectral analyses, showed that the fluctuation of standing watch time reports data exhibits chaotic and fractal system properties. The critical implications of the study findings for the human-centered design of complex systems were also discussed.

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.

Selection Procedures for the Largest Lyapunov Exponent in Gait Biomechanics

The present study was aimed at investigating the effectiveness of the Wolf et al. (LyE_W) and Rosenstein et al. largest Lyapunov Exponent (LyE_R) algorithms to differentiate data sets with distinctly different temporal structures. The three-dimensional displacement of the sacrum was recorded from healthy subjects during walking and running at two speeds; one low speed close to the preferred walking speed and one high speed close to the preferred running speed. LyE_R and LyE_W were calculated using four different time series normalization procedures. The performance of the algorithms were evaluated based on their ability to return relative low values for slow walking and fast running and relative high values for fast walking and slow running. Neither of the two algorithms outperformed the other; however, the effectiveness of the two algorithms was highly dependent on the applied time series normalization procedure. Future studies using the LyE_R should normalize the time series to a fixed number of strides and a fixed number of data points per stride or data points per time series while the LyE_W should be applied to time series normalized to a fixed number of data points or a fixed number of strides.

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.

Understanding Eye Movement Signal Characteristics Based on Their Dynamical and Fractal Features

Eye movement is one of the biological signals whose exploration may reveal substantial information, enabling greater understanding of the biology of the brain and its mechanisms. In this research, eye movement dynamics were studied in terms of chaotic behavior and self-similarity assessment to provide a description of young, healthy, oculomotor system characteristics. The first of the investigated features is present and advantageous for many biological objects or physiological phenomena, and its vanishing or diminishment may indicate a system pathology. Similarly, exposed self-similarity may prove useful for indicating a young and healthy system characterized by adaptability. For this research, 24 young people with normal vision were involved. Their eye movements were registered with the usage of a head-mounted eye tracker, using infrared oculography, embedded in the sensor, measuring the rotations of the left and the right eye. The influence of the preprocessing step in the form of the application of various filtering methods on the assessment of the final dynamics was also explored. The obtained results confirmed the existence of chaotic behavior in some parts of eye movement signal; however, its strength turned out to be dependent on the filter used. They also exposed the long-range correlation representing self-similarity, although the influence of the applied filters on these outcomes was not unveiled.

Maximum Lyapunov exponent revisited: Long-term attractor divergence of gait dynamics is highly sensitive to the noise structure of stride intervals

BACKGROUND

The local dynamic stability method (maximum Lyapunov exponent) can assess gait stability. Two variants of the method exist: the short-term divergence exponent (DE), and the long-term DE. Only the short-term DE can predict fall risk. However, the significance of long-term DE has been unclear so far. Some studies have suggested that the complex, fractal-like structure of fluctuations among consecutive strides correlates with long-term DE. The aim, therefore, was to assess whether the long-term DE is a gait complexity index.

METHODS

The study reanalyzed a dataset of trunk accelerations from 100 healthy adults walking at preferred speed on a treadmill for 10 min. By interpolation, the stride intervals were modified within the acceleration signals for the purpose of conserving the original shape of the signal, while imposing a known stride-to-stride fluctuation structure. Four types of hybrid signals with different noise structures were built: constant, anti-correlated, random, and correlated (fractal). Short- and long-term DEs were then computed.

RESULTS

The results show that long-term DEs, but not short-term DEs, are sensitive to the noise structure of stride intervals. For example, it was that observed that random hybrid signals exhibited significantly lower long-term DEs than hybrid correlated signals did (0.100 vs 0.144, i.e. a 44% difference). Long-term DEs from constant hybrid signals were close to zero (0.006). Conversely, short-term DEs of anti-correlated, random, and correlated hybrid signals were closely grouped (2.49, 2.50, and 2.51).

CONCLUSIONS

The short-term DE and the long-term DE, although they are both computed from divergence curves, should not be interpreted in a similar way. The long-term DE is very likely an index of gait complexity, which may be associated with gait automaticity or cautiousness. Consequently, to better differentiate between short- and long-term DEs, the use of the term attractor complexity index (ACI) is proposed for the latter.

Effect of Rhythmic Auditory Cueing on Aging Gait: A Systematic Review and Meta-Analysis

Rhythmic auditory cueing has been widely used in gait rehabilitation over the past decade. The entrainment effect has been suggested to introduce neurophysiological changes, alleviate auditory-motor coupling and reduce cognitive-motor interferences. However, a consensus as to its influence over aging gait is still warranted. A systematic review and meta-analysis was carried out to analyze the effects of rhythmic auditory cueing on spatiotemporal gait parameters among healthy young and elderly participants. This systematic identification of published literature was performed according to PRISMA guidelines, from inception until May 2017, on online databases: Web of science, PEDro, EBSCO, MEDLINE, Cochrane, EMBASE, and PROQUEST. Studies were critically appraised using PEDro scale. Of 2789 records, 34 studies, involving 854 (499 young/355 elderly) participants met our inclusion criteria. The meta-analysis revealed enhancements in spatiotemporal parameters of gait i.e. gait velocity (Hedge's g: 0.85), stride length (0.61), and cadence (1.1), amongst both age groups. This review, for the first time, evaluates the effects of auditory entrainment on aging gait and discusses its implications under higher and lower information processing constraints. Clinical implications are discussed with respect to applications of auditory entrainment in rehabilitation settings.

Sample Entropy of Human Gait Center of Pressure Displacement: A Systematic Methodological Analysis

Sample entropy (SampEn) has been used to quantify the regularity or predictability of human gait signals. There are studies on the appropriate use of this measure for inter-stride spatio-temporal gait variables. However, the sensitivity of this measure to preprocessing of the signal and to variant values of template size (m), tolerance size (r), and sampling rate has not been studied when applied to “whole” gait signals. Whole gait signals are the entire time series data obtained from force or inertial sensors. This study systematically investigates the sensitivity of SampEn of the center of pressure displacement in the mediolateral direction (ML COP-D) to variant parameter values and two pre-processing methods. These two methods are filtering the high-frequency components and resampling the signals to have the same average number of data points per stride. The discriminatory ability of SampEn is studied by comparing treadmill walk only (WO) to dual-task (DT) condition. The results suggest that SampEn maintains the directional difference between two walking conditions across variant parameter values, showing a significant increase from WO to DT condition, especially when signals are low-pass filtered. Moreover, when gait speed is different between test conditions, signals should be low-pass filtered and resampled to have the same average number of data points per stride.

The Effects of Aging and Dual Tasking on Human Gait Complexity During Treadmill Walking: A Comparative Study Using Quantized Dynamical Entropy and Sample Entropy

Quantized dynamical entropy (QDE) has recently been proposed as a new measure to quantify the complexity of dynamical systems with the purpose of offering a better computational efficiency. This paper further investigates the viability of this method using five different human gait signals. These signals are recorded while normal walking and while performing secondary tasks among two age groups (young and older age groups). The results are compared with the outcomes of previously established sample entropy (SampEn) measure for the same signals. We also study how analyzing segmented and spatially and temporally normalized signal differs from analyzing whole data. Our findings show that human gait signals become more complex as people age and while they are cognitively loaded. Center of pressure (COP) displacement in mediolateral direction is the best signal for showing the gait changes. Moreover, the results suggest that by segmenting data, more information about intrastride dynamical features are obtained. Most importantly, QDE is shown to be a reliable measure for human gait complexity analysis.

Effects of backpack load and positioning on nonlinear gait features in young adults

Overloaded backpacks can cause changes in posture and gait dynamic balance. Therefore, the aim of this study was to assess gait regularity and local dynamic stability in young adults as they carried a backpack in different positions, and with different loads. Twenty-one healthy young adults participated in the study, carrying a backpack that was loaded with 10 and 20% of their body weight (BW). The participants walked on a level treadmill at their preferred walking speeds for 4 min under different conditions of backpack load and position (i.e. with backpack positioned back bilaterally, back unilaterally, frontally or without a backpack). Results indicate that backpack load and positioning significantly influence gait stability and regularity, with the exception of the 10% BW bilateral back position. Therefore, the recommended safe load for school-age children and adolescents (10% of BW) should also be considered for young adults. Practitioner summary: Increase in load results in changes in posture, muscle activity and gait parameters, so we investigated the gait adaptations related to regularity and stability. Conditions with high backpack loads significantly influenced gait stability and regularity in a position-dependent manner, except for 10% body weight bilateral back position.

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.

Challenging human locomotion: stability and modular organisation in unsteady conditions

The need to move over uneven terrain is a daily challenge. In order to face unexpected perturbations due to changes in the morphology of the terrain, the central nervous system must flexibly modify its control strategies. We analysed the local dynamic stability and the modular organisation of muscle activation (muscle synergies) during walking and running on an even- and an uneven-surface treadmill. We hypothesized a reduced stability during uneven-surface locomotion and a reorganisation of the modular control. We found a decreased stability when switching from even- to uneven-surface locomotion (p < 0.001 in walking, p = 0.001 in running). Moreover, we observed a substantial modification of the time-dependent muscle activation patterns (motor primitives) despite a general conservation of the time-independent coefficients (motor modules). The motor primitives were considerably wider in the uneven-surface condition. Specifically, the widening was significant in both the early (+40.5%, p < 0.001) and late swing (+7.7%, p = 0.040) phase in walking and in the weight acceptance (+13.6%, p = 0.006) and propulsion (+6.0%, p = 0.041) phase in running. This widening highlighted an increased motor output’s robustness (i.e. ability to cope with errors) when dealing with the unexpected perturbations. Our results confirmed the hypothesis that humans adjust their motor control strategies’ timing to deal with unsteady locomotion.

Searching for Chaos Evidence in Eye Movement Signals

Most naturally-occurring physical phenomena are examples of nonlinear dynamic systems, the functioning of which attracts many researchers seeking to unveil their nature. The research presented in this paper is aimed at exploring eye movement dynamic features in terms of the existence of chaotic nature. Nonlinear time series analysis methods were used for this purpose. Two time series features were studied: fractal dimension and entropy, by utilising the embedding theory. The methods were applied to the data collected during the experiment with “jumping point” stimulus. Eye movements were registered by means of the Jazz-novo eye tracker. One thousand three hundred and ninety two (1392) time series were defined, based on the horizontal velocity of eye movements registered during imposed, prolonged fixations. In order to conduct detailed analysis of the signal and identify differences contributing to the observed patterns of behaviour in time scale, fractal dimension and entropy were evaluated in various time series intervals. The influence of the noise contained in the data and the impact of the utilized filter on the obtained results were also studied. The low pass filter was used for the purpose of noise reduction with a 50 Hz cut-off frequency, estimated by means of the Fourier transform and all concerned methods were applied to time series before and after noise reduction. These studies provided some premises, which allow perceiving eye movements as observed chaotic data: characteristic of a space-time separation plot, low and non-integer time series dimension, and the time series entropy characteristic for chaotic systems.

Short- and long-term effects of altered point of ground reaction force application on human running energetics

The current study investigates an acute and a gradual transition of the point of force application (PFA) from the rearfoot towards the fore of the foot during running, on the rate of metabolic energy consumption. The participants were randomly assigned in two experimental and one control groups: a short-term intervention group (STI, N=17; two training sessions), a long-term intervention group (LTI, N=10; 14-week gradual transition) and a control group (CG, N=11). Data were collected at two running velocities (2.5 and 3.0 m/s). The cost coefficient (i.e. energy required for a unit of vertical ground reaction force, J/N) decreased (p&lt;0.001) after both interventions due to a more anterior PFA during running (STI:12%, LTI:11%), but led to a higher (p&lt;0.001) rate of force generation (STI:17%, LTI:15.2%). Dynamic stability of running showed a significant (p&lt;0.001) decrease in the STI (2.1%), but no differences (p=0.673) in the LTI. The rate of metabolic energy consumption increased in the STI (p=0.038), but remained unchanged in the LTI (p=0.660). The control group had no changes. These results demonstrate that the cost coefficient was successfully decreased following an alteration in the running technique towards a more anterior PFA. However, the energy consumption remained unchanged because of a simultaneous increase in rate of force generation due to a decreased contact time per step. The increased instability found during the short-term intervention and its neutralization after the long-term intervention indicates a role of motor control errors in the economy of running after acute alterations in habitual running execution.

The Applicability of Rhythm-Motor Tasks to a New Dual Task Paradigm for Older Adults

Given the interplay between cognitive and motor functions during walking, cognitive demands required during gait have been investigated with regard to dual task performance. Along with the needs to understand how the type of concurrent task while walking affects gait performance, there are calls for diversified dual tasks that can be applied to older adults with varying levels of cognitive decline. Therefore, this study aimed to examine how rhythm-motor tasks affect dual task performance and gait control, compared to a traditional cognitive-motor task. Also, it examined whether rhythm-motor tasks are correlated with traditional cognitive-motor task performance and cognitive measures. Eighteen older adults without cognitive impairment participated in this study. Each participant was instructed to walk at self-paced tempo without performing a concurrent task (single walking task) and walk while separately performing two types of concurrent tasks: rhythm-motor and cognitive-motor tasks. Rhythm-motor tasks included instrument playing (Walk_IP), matching to rhythmic cueing (Walk_RC), and instrument playing while matching to rhythmic cueing (Walk_IP+RC). The cognitive-motor task involved counting forward by 3s (Walk_Count.f3). In each condition, dual task costs (DTC), a measure for how dual tasks affect gait parameters, were measured in terms of walking speed and stride length. The ratio of stride length to walking speed, a measure for dynamic control of gait, was also examined. The results of this study demonstrated that the task type was found to significantly influence these measures. Rhythm-motor tasks were found to interfere with gait parameters to a lesser extent than the cognitive-motor task (Walk_Count.f3). In terms of ratio measures, stride length remained at a similar level, walking speed greatly decreased in the Walk_Count.f3 condition. Significant correlations between dual task-related measures during rhythm-motor and cognitive-motor tasks support the potential of applying rhythm-motor tasks to dual task methodology. This study presents how rhythm-motor tasks demand cognitive control at different levels than those engaged by cognitive-motor tasks. It also indicates how these new dual tasks can effectively mediate dual task performance indicative of fall risks, while requiring increased cognitive resources but facilitating gait control as a compensatory strategy to maintain gait stability.

Determinants of gait stability while walking on a treadmill: A machine learning approach

Dynamic balance in human locomotion can be assessed through the local dynamic stability (LDS) method. Whereas gait LDS has been used successfully in many settings and applications, little is known about its sensitivity to individual characteristics of healthy adults. Therefore, we reanalyzed a large dataset of accelerometric data measured for 100 healthy adults from 20 to 70 years of age performing 10 min treadmill walking. We sought to assess the extent to which the variations of age, body mass and height, sex, and preferred walking speed (PWS) could influence gait LDS. The random forest (RF) and multiple adaptive regression splines (MARS) algorithms were selected for their good bias-variance tradeoff and their capabilities to handle nonlinear associations. First, through variable importance measure (VIM), we used RF to evaluate which individual characteristics had the highest influence on gait LDS. Second, we used MARS to detect potential interactions among individual characteristics that may influence LDS. The VIM and MARS results indicated that PWS and age correlated with LDS, whereas no associations were found for sex, body height, and body mass. Further, the MARS model detected an age by PWS interaction: on one hand, at high PWS, gait stability is constant across age while, on the other hand, at low PWS, gait instability increases substantially with age. We conclude that it is advisable to consider the participants' age as well as their PWS to avoid potential biases in evaluating dynamic balance through LDS.

Can Tai Chi training impact fractal stride time dynamics, an index of gait health, in older adults? Cross-sectional and randomized trial studies

Purpose

To determine if Tai Chi (TC) has an impact on long-range correlations and fractal-like scaling in gait stride time dynamics, previously shown to be associated with aging, neurodegenerative disease, and fall risk.

Methods

Using Detrended Fluctuation Analysis (DFA), this study evaluated the impact of TC mind-body exercise training on stride time dynamics assessed during 10 minute bouts of overground walking. A hybrid study design investigated long-term effects of TC via a cross-sectional comparison of 27 TC experts (24.5 ± 11.8 yrs experience) and 60 age- and gender matched TC-naïve older adults (50–70 yrs). Shorter-term effects of TC were assessed by randomly allocating TC-naïve participants to either 6 months of TC training or to a waitlist control. The alpha (α) long-range scaling coefficient derived from DFA and gait speed were evaluated as outcomes.

Results

Cross-sectional comparisons using confounder adjusted linear models suggest that TC experts exhibited significantly greater long-range scaling of gait stride time dynamics compared with TC-naïve adults. Longitudinal random-slopes with shared baseline models accounting for multiple confounders suggest that the effects of shorter-term TC training on gait dynamics were not statistically significant, but trended in the same direction as longer-term effects although effect sizes were very small. In contrast, gait speed was unaffected in both cross-sectional and longitudinal comparisons.

Conclusion

These preliminary findings suggest that fractal-like measures of gait health may be sufficiently precise to capture the positive effects of exercise in the form of Tai Chi, thus warranting further investigation. These results motivate larger and longer-duration trials, in both healthy and health-challenged populations, to further evaluate the potential of Tai Chi to restore age-related declines in gait dynamics.

Trial registration

The randomized trial component of this study was registered at ClinicalTrials.gov (NCT01340365).

Monitoring of Gait Quality in Patients With Chronic Pain of Lower Limbs

Severe injuries of lower extremities often lead to chronic pain and reduced walking abilities. We postulated that measuring free-living gait can provide further information about walking ability in complement to clinical evaluations. We sought to validate a method that characterizes free gaits with a wearable sensor. Over one week, 81 healthy controls (HC) and 66 chronic lower limb pain patients (CLLPP) hospitalized for multidisciplinary rehabilitation wore a simple accelerometer (Actigraph). In the acceleration signals, steady 1-min walks detected numbered 7,835 (5,085 in CLLPP and 2,750 in HC). Five gait quality measures were assessed: movement intensity, cadence, stride regularity, and short-term and long-term local dynamic stability. Gait quality variables differed significantly between CLLPP and HC (4%-26%). Intraclass correlation coefficients revealed moderate to high repeatability (0.71-0.91), which suggests that seven days of measurement are sufficient to assess average gait patterns. Regression analyses showed significant association (R² = 0.44) between the gait quality variables and a clinical evaluation of walking ability, i.e., the 6-min walk test. Overall, the results show that the method is easy to implement, valid (high concurrent validity), and reliable to assess walking abilities ecologically.

Goal equivalent manifold analysis of task performance in non-specific LBP and healthy subjects during repetitive trunk movement: Effect of load, velocity, symmetry

Motor abundance allows reliability of motor performance despite its variability. The nature of this variability provides important information on the flexibility of control strategies. This feature of control may be affected by low back pain (LPB) and trunk flexion/extension conditions. Goal equivalent manifold (GEM) analysis was used to quantify the ability to exploit motor abundance during repeated trunk flexion/extension in healthy individuals and people with chronic non-specific LBP (CNSLBP). Kinematic data were collected from 22 healthy volunteers and 22 CNSLBP patients during metronomically timed, repeated trunk flexion/extension in three conditions of symmetry, velocity, and loading; each at two levels. A goal function for the task was defined as maintaining a constant movement time at each cycle. Given the GEM, flexibility index and performance index were calculated respectively as amounts of goal-equivalent variability and the ratio of goal-equivalent to non-goal-equivalent variability. CNSLBP group was as similar as healthy individuals in both flexibility index (p=0.41) and performance index (p=0.24). Performance index was higher in asymmetric (p<0.001), high velocity (p<0.001), and loaded (p=0.006) conditions. Performance and flexibility in using motor abundance were influenced by repeated trunk flexion/extension conditions. However, these measures were not significantly affected by CNSLBP.

Fractal Fluctuations in Human Walking: Comparison Between Auditory and Visually Guided Stepping

In human locomotion, sensorimotor synchronization of gait consists of the coordination of stepping with rhythmic auditory cues (auditory cueing, AC). AC changes the long-range correlations among consecutive strides (fractal dynamics) into anti-correlations. Visual cueing (VC) is the alignment of step lengths with marks on the floor. The effects of VC on the fluctuation structure of walking have not been investigated. Therefore, the objective was to compare the effects of AC and VC on the fluctuation pattern of basic spatiotemporal gait parameters. Thirty-six healthy individuals walked 3 × 500 strides on an instrumented treadmill with augmented reality capabilities. The conditions were no cueing (NC), AC, and VC. AC included an isochronous metronome. For VC, projected stepping stones were synchronized with the treadmill speed. Detrended fluctuation analysis assessed the correlation structure. The coefficient of variation (CV) was also assessed. The results showed that AC and VC similarly induced a strong anti-correlated pattern in the gait parameters. The CVs were similar between the NC and AC conditions but substantially higher in the VC condition. AC and VC probably mobilize similar motor control pathways and can be used alternatively in gait rehabilitation. However, the increased gait variability induced by VC should be considered.

How to Sync to the Beat of a Persistent Fractal Metronome without Falling Off the Treadmill?

In rehabilitation, rhythmic acoustic cues are often used to improve gait. However, stride-time fluctuations become anti-persistent with such pacing, thereby deviating from the characteristic persistent long-range correlations in stride times of self-paced walking healthy adults. Recent studies therefore experimented with metronomes with persistence in interbeat intervals and successfully evoked persistent stride-time fluctuations. The objective of this study was to examine how participants couple their gait to a persistent metronome, evoking persistently longer or shorter stride times over multiple consecutive strides, without wandering off the treadmill. Twelve healthy participants walked on a treadmill in self-paced, isochronously paced and non-isochronously paced conditions, the latter with anti-persistent, uncorrelated and persistent correlations in interbeat intervals. Stride-to-stride fluctuations of stride times, stride lengths and stride speeds were assessed with detrended fluctuation analysis, in conjunction with an examination of the coupling between stride times and stride lengths. Stride-speed fluctuations were anti-persistent for all conditions. Stride-time and stride-length fluctuations were persistent for self-paced walking and anti-persistent for isochronous pacing. Both stride times and stride lengths changed from anti-persistence to persistence over the four non-isochronous metronome conditions, accompanied by an increasingly stronger coupling between these gait parameters, with peak values for the persistent metronomes. These results revealed that participants were able to follow the beat of a persistent metronome without falling off the treadmill by strongly coupling stride-length fluctuations to the stride-time fluctuations elicited by persistent metronomes, so as to prevent large positional displacements along the treadmill. For self-paced walking, in contrast, this coupling was very weak. In combination, these results challenge the premise that persistent metronomes in gait rehabilitation would evoke stride-to-stride dynamics reminiscent of self-paced walking healthy adults. Future studies are recommended to include an analysis of the interrelation between stride times and stride lengths in addition to the correlational structure of either one in isolation.

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

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

Could local dynamic stability serve as an early predictor of falls in patients with moderate neurological gait disorders? A reliability and comparison study in healthy individuals and in patients with paresis of the lower extremities

Falls while walking are frequent in patients with muscular dysfunction resulting from neurological disorders. Falls induce injuries that may lead to deconditioning and disabilities, which further increase the risk of falling. Therefore, an early gait stability index would be useful to evaluate patients in order to prevent the occurrence of future falls. Derived from chaos theory, local dynamic stability (LDS), defined by the maximal Lyapunov exponent, assesses the sensitivity of a dynamic system to small perturbations. LDS has already been used for fall risk prediction in elderly people. The aim of the present study was to provide information to facilitate future researches regarding gait stability in patients with neurological gait disorders. The main objectives were 1) to evaluate the intra-session repeatability of LDS in patients and 2) to assess the discriminative power of LDS to differentiate between healthy individuals and neurological patients. Eighty-three patients with mild to moderate neurological disorders associated with paresis of the lower extremities and 40 healthy controls participated in the study. The participants performed 2×30 s walking wearing a 3D accelerometer attached to the lower back, from which 2×35 steps were extracted. LDS was defined as the average exponential rate of divergence among trajectories in a reconstructed state-space that reflected the gait dynamics. LDS assessed along the medio-lateral axis offered the highest repeatability and discriminative power. Intra-session repeatability (intraclass correlation coefficient between the two repetitions) in the patients was 0.89 and the smallest detectable difference was 16%. LDS was substantially lower in the patients than in the controls (33% relative difference, standardized effect size 2.3). LDS measured in short over-ground walking tests seems sufficiently reliable. LDS exhibits good discriminative power to differentiate fall-prone individuals and opens up the possibility of future clinical applications for better prediction of fall risk in neurological patients.

'Human paced' walking: followers adopt stride time dynamics of leaders

Isochronous cueing is widely used in gait rehabilitation even though it alters the stride-time dynamics toward anti-persistent rather than the persistent, fractal fluctuations characteristic of human walking. In the present experiment we tested an alternative cueing method: pacing by a human. To this end, we formed sixteen pairs of walkers based on their preferred stride frequency. Each pair consisted of a designated "leader" and a "follower" who was instructed to synchronize his or her steps to those of the leader. Heel strike times were detected with tiny footswitches, and Detrended Fluctuation Analysis (DFA) was applied to estimate fractal exponents of stride-time series. To ensure that the stride-time dynamics of the follower matched those of the leader, the latter was structurally modified by artificial cueing via either an isochronous metronome or a fractal metronome, in contrast to self-paced walking. Mean relative phases between followers and leaders were close to 0°, confirming that followers effectively synchronized their footfalls with those of the leaders. Mean fractal exponents were not statistically different between followers and leaders in any condition and highly correlated, suggesting that followers matched their stride-time structure to that of leaders. Our results open perspectives for alternative, more natural cueing protocols for gait rehabilitation.