The impact of speed and time on gait dynamics

Gait signature changes with walking speed are similar among able-bodied young adults despite persistent individual-specific differences

Understanding individuals' distinct movement patterns is crucial for health, rehabilitation, and sports. Recently, we developed a machine learning-based framework to show that "gait signatures" describing the neuromechanical dynamics governing able-bodied and post-stroke gait kinematics remain individual-specific across speeds. However, we only evaluated gait signatures within a limited speed range and number of participants, using only sagittal plane (i.e., 2D) joint angles. Here we characterized changes in gait signatures across a wide range of speeds, from very slow (0.3 m/s) to exceptionally fast (above the walk-to-run transition speed) in 17 able-bodied young adults. We further assessed whether 3D kinematic and/or kinetic (ground reaction forces, joint moments, and powers) data would improve the discrimination of gait signatures. Our study showed that gait signatures remained individual-specific across walking speeds: Notably, 3D kinematic signatures achieved exceptional accuracy (99.8%, confidence interval (CI) 99.1-100%) in classifying individuals, surpassing both 2D kinematics and 3D kinetics. Moreover, participants exhibited consistent, predictable linear changes in their gait signatures across the entire speed range. These changes were associated with participants' preferred walking speeds, balance ability, cadence, and step length. These findings support gait signatures as a tool to characterize individual differences in gait and predict speed-induced changes in gait dynamics.

Gait signature changes with walking speed are similar among able-bodied young adults despite persistent individual-specific differences

Understanding individuals' distinct movement patterns is crucial for health, rehabilitation, and sports. Recently, we developed a machine learning-based framework to show that "gait signatures" describing the neuromechanical dynamics governing able-bodied and post-stroke gait kinematics remain individual-specific across speeds. However, we only evaluated gait signatures within a limited speed range and number of participants, using only sagittal plane (i.e., 2D) joint angles. Here we characterized changes in gait signatures across a wide range of speeds, from very slow (0.3 m/s) to exceptionally fast (above the walk-to-run transition speed) in 17 able-bodied young adults. We further assessed whether 3D kinematic and/or kinetic (ground reaction forces, joint moments, and powers) data would improve the discrimination of gait signatures. Our study showed that gait signatures remained individual-specific across walking speeds: Notably, 3D kinematic signatures achieved exceptional accuracy (99.8%, confidence interval (CI): 99.1-100%) in classifying individuals, surpassing both 2D kinematics and 3D kinetics. Moreover, participants exhibited consistent, predictable linear changes in their gait signatures across the entire speed range. These changes were associated with participants' preferred walking speeds, balance ability, cadence, and step length. These findings support gait signatures as a tool to characterize individual differences in gait and predict speed-induced changes in gait dynamics.

Nonlinear Analysis of the Hand and Foot Force-Time Profiles in the Four Competitive Swimming Strokes

Human locomotion on water depends on the force produced by the swimmer to propel the body forward. Performance of highly complex motor tasks like swimming can yield minor variations that only nonlinear analysis can be sensitive enough to detect. The purpose of the present study was to examine the nonlinear properties of the hand/feet forces and describe their variations across the four competitive swimming strokes performing segmental and full-body swimming. Swimmers performed all-out bouts of 25 m in the four swimming strokes, swimming the full-body stroke, with the arm-pull only and with the leg kicking only. Hand/foot force and swimming velocity were measured. The Higuchi's fractal dimension (HFD) and sample entropy (SampEn) were used for the nonlinear analysis of force and velocity. Both the arm-pull and leg kicking alone were found to produce similar peak and mean hand/foot forces as swimming the full-body stroke. Hand force was more complex in breaststroke and butterfly stroke; conversely, kicking conditions were more complex in front crawl and backstroke. Moreover, the arm-pull and kicking alone tended to be more complex (higher HFD) but more predictable (lower SampEn) than while swimming the full-body stroke. There was no loss of force production from segmental swimming to the full-body counterpart. In conclusion, the number of segments in action influences the nonlinear behavior of the force produced and, when combining the four limbs, the complexity of the hand/foot force tends to decrease.

A Dynamical Systems Approach to Characterizing Brain-Body Interactions during Movement: Challenges, Interpretations, and Recommendations

Brain-body interactions (BBIs) have been the focus of intense scrutiny since the inception of the scientific method, playing a foundational role in the earliest debates over the philosophy of science. Contemporary investigations of BBIs to elucidate the neural principles of motor control have benefited from advances in neuroimaging, device engineering, and signal processing. However, these studies generally suffer from two major limitations. First, they rely on interpretations of 'brain' activity that are behavioral in nature, rather than neuroanatomical or biophysical. Second, they employ methodological approaches that are inconsistent with a dynamical systems approach to neuromotor control. These limitations represent a fundamental challenge to the use of BBIs for answering basic and applied research questions in neuroimaging and neurorehabilitation. Thus, this review is written as a tutorial to address both limitations for those interested in studying BBIs through a dynamical systems lens. First, we outline current best practices for acquiring, interpreting, and cleaning scalp-measured electroencephalography (EEG) acquired during whole-body movement. Second, we discuss historical and current theories for modeling EEG and kinematic data as dynamical systems. Third, we provide worked examples from both canonical model systems and from empirical EEG and kinematic data collected from two subjects during an overground walking task.

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.

Gait analysis under the lens of statistical physics

Human gait is a fundamental activity, essential for the survival of the individual, and an emergent property of the interactions between complex physical and cognitive processes. Gait is altered in many situations, due both to external constraints, as e.g. paced walk, and to physical and neurological pathologies. Its study is therefore important as a way of improving the quality of life of patients, but also as a door to understanding the inner working of the human nervous system. In this review we explore how four statistical physics concepts have been used to characterise normal and pathological gait: entropy, maximum Lyapunov exponent, multi-fractal analysis and irreversibility. Beyond some basic definitions, we present the main results that have been obtained in this field, as well as a discussion of the main limitations researchers have dealt and will have to deal with. We finally conclude with some biomedical considerations and avenues for further development.

Entropy Analysis in Gait Research: Methodological Considerations and Recommendations

The usage of entropy analysis in gait research has grown considerably the last two decades. The present paper reviews the application of different entropy analyses in gait research and provides recommendations for future studies. While single-scale entropy analysis such as approximate and sample entropy can be used to quantify regularity/predictability/probability, they do not capture the structural richness and component entanglement characterized by a complex system operating across multiple spatial and temporal scales. Thus, for quantification of complexity, either multiscale entropy or refined composite multiscale entropy is recommended. For both single- and multiscale-scale entropy analyses, care should be made when selecting the input parameters of tolerance window r, vector length m, time series length N and number of scales. This selection should be based on the proposed research question and the type of data collected and not copied from previous studies. Parameter consistency should be investigated and published along with the main results to ensure transparency and enable comparisons between studies. Furthermore, since the interpretation of the absolute size of both single- and multiscale entropy analyses outcomes is not straightforward, comparisons should always be made with a control condition or group.

The effects of walking speed and mobile phone use on the walking dynamics of young adults

Walking while using a mobile phone has been shown to affect the walking dynamics of young adults. However, this has only been investigated using treadmill walking at a fixed walking speed. In this study, the dynamics of over ground walking were investigated using lower trunk acceleration measured over 12 consecutive trials, following differing walking speed and mobile phone use instructions. Higher walking speed significantly increased the proportion of acceleration along the vertical measurement axis, while decreasing the proportion of acceleration along the anteroposterior axis (p < 0.001). Moreover, higher walking speed also resulted in increased sample entropy along all measurement axes (p < 0.05). When walking while texting, the maximum Lyapunov exponent increased along the anteroposterior and vertical measurement axes (p < 0.05), while sample entropy decreased significantly along the vertical axis (p < 0.001). Walking speed and mobile phone use both affect the walking dynamics of young adults. Walking while texting appears to produce a reduction in local dynamic stability and an increase in regularity, however, caution is required when interpreting the extent of this task effect, since walking speed also affected walking dynamics.

Test-Retest Reliability and the Effects of Walking Speed on Stride Time Variability During Continuous, Overground Walking in Healthy Young Adults

Studies have investigated the reliability and effect of walking speed on stride time variability during walking trials performed on a treadmill. The objective of this study was to investigate the reliability of stride time variability and the effect of walking speed on stride time variability, during continuous, overground walking in healthy young adults. Participants completed: (1) 2 walking trials at their preferred walking speed on 1 day and another trial 2 to 4 days later and (2) 1 trial at their preferred walking speed, 1 trial approximately 20% to 25% faster than their preferred walking speed, and 1 trial approximately 20% to 25% slower than their preferred walking speed on a separate day. Data from a waist-mounted accelerometer were used to determine the consecutive stride times for each trial. The reliability of stride time variability outcomes was generally poor (intraclass correlations: .167-.487). Although some significant differences in stride time variability were found between the preferred walking speed, fast, and slow trials, individual between-trial differences were generally below the estimated minimum difference considered to be a real difference. The development of a protocol to improve the reliability of stride time variability outcomes during continuous, overground walking would be beneficial to improve their application in research and clinical settings.

Leg-amplitude differentiation guided by haptic and visual feedback to detect alterations in motor flexibility due to Total Knee Replacement

Following total knee replacement (TKR), patients often persist in maladaptive motor behavior which they developed before surgery to cope with symptoms of osteoarthritis. An important challenge in physical therapy is to detect, recognize and change such undesired movement behavior. The goal of this study was to measure the differences in clinical status of patients pre-TKR and post-TKR and to investigate if differences in clinical status were accompanied by differences in the patients'' motor flexibility. Eleven TKR participants were measured twice: pre-TKR and post-TKR (twenty weeks after TKR). In order to infer maladaptation, the pre-TKR and post-TKR measurements of the patient group were separately compared to one measurement in a control group of fourteen healthy individuals. Clinical status was measured with the Visual Analogue Scale (VAS) for pain and knee stiffness and the Knee Injury and Osteoarthritis Outcome Score (KOOS). Furthermore, Lower-limb motor flexibility was assessed by means of a treadmill walking task and a leg-amplitude differentiation task (LAD-task) supported by haptic or visual feedback. Motor flexibility was measured by coordination variability (standard deviation (SD) of relative phase between the legs) and temporal variability (sample entropy) of both leg movements. In the TKR-group, the VAS-pain and VAS- stiffness and the subscales of the KOOS significantly decreased after TKR. In treadmill walking, lower-limb motor flexibility did not significantly change after TKR. Between-leg coordination variability was significantly lower post-TKR compared to controls. In the LAD-task, a significant decrease of between-leg coordination variability between pre-TKR and post-TKR was accompanied by a significant increase in temporal variability. Post-TKR-values of lower-limb flexibility approached the values of the control group. The results demonstrate that a clinically relevant change in clinical status, twenty weeks after TKR, is not accompanied by alterations in lower-limb motor flexibility during treadmill walking but is accompanied by changes in motor flexibility towards the level of healthy controls during a LAD-task with visual and haptic feedback. Challenging patients with non-preferred movements such as amplitude differentiation may be a promising tool in clinical assessment of motor flexibility following TKR.

Sampling frequency influences sample entropy of kinematics during walking

Sample entropy (SaEn) has been used to assess the regularity of lower limb joint angles during walking. However, changing sampling frequency and the number of included strides can potentially affect the outcome. The present study investigated the effect of sample frequency and the number of included strides on the calculations of SaEn in joint angle signals recorded during treadmill walking. Eleven subjects walked at their preferred walking speed for 10 min, and SaEn was calculated on sagittal plane hip, knee, and ankle angle signals extracted from 50, 100, 200, 300, and 400 strides at sampling frequencies of 60, 120, 240, and 480 Hz. Increase in sampling frequency decreased the SaEn significantly for the three joints. The number of included strides had no effect on the SaEn calculated on the hip joint angle and only limited effect on the SaEn calculated on the knee and ankle joint signals. The present study suggests that the number of data points within each stride to a greater extent determines the size of the SaEn compared to the number of strides and emphasizes the use of a fixed number of data points within each stride when applying SaEn to lower limb joint angles during walking. Graphical abstract Sampling frequency influences sample entropy of kinematics during walking.

Does motor expertise facilitate amplitude differentiation of lower limb-movements in an asymmetrical bipedal coordination task?

The motor system's natural tendency is to move the limbs over equal amplitudes, for example in walking. However, in many situations in which people must perform complex movements, a certain degree of amplitude differentiation of the limbs is required. Visual and haptic feedback have recently been shown to facilitate such independence of limb movements. However, it is unknown whether motor expertise moderates the extent to which individuals are able to differentiate the amplitudes of their limb-movements while being supported with visual and haptic feedback. To answer this question 14 pre-professional dancers were compared to 14 non-dancers on simultaneously generating a small displacement with one foot, and a larger one with the other foot, in four different feedback conditions. In two conditions, haptic guidance was offered, either in a passive or active mode. In the other two conditions, veridical and enhanced visual feedback were provided. Surprisingly, no group differences were found regarding the degree to which the visual or haptic feedback assisted the generation of the different target amplitudes of the feet (mean amplitude difference between the feet). The correlation between the displacements of the feet and the standard deviation of the continuous relative phase between the feet, reflecting the degree of independence of the feet movements, also failed to show between-group differences. Sample entropy measures, indicating the predictability of the foot movements, did show a group difference. In the haptically-assisted conditions, the dancers demonstrated more predictable coordination patterns than the non-dancers as reflected by lower sample entropy values whereas the reverse was true in the visual-feedback conditions. The results demonstrate that motor expertise does not moderate the extent to which haptic tracking facilitates the differentiation of the amplitudes of the lower limb movements in an asymmetrical bipedal coordination task.

A systematic review of the gait characteristics associated with Cerebellar Ataxia

BACKGROUND

Cerebellar Ataxias are a group of gait disorders resulting from dysfunction of the cerebellum, commonly characterised by slowly progressing incoordination that manifests as problems with balance and walking leading to considerable disability. There is increasing acceptance of gait analysis techniques to quantify subtle gait characteristics that are unmeasurable by current clinical methods This systematic review aims to identify the gait characteristics able to differentiate between Cerebellar Ataxia and healthy controls.

METHODS

Following systematic search and critical appraisal of the literature, gait data relating to preferred paced walking in Cerebellar Ataxia was extracted from 21 studies. A random-effect model meta-analysis was performed for 14 spatiotemporal parameters. Quality assessment was completed to detect risk of bias.

RESULTS

There is strong evidence that compared with healthy controls, Cerebellar Ataxia patients walk with a reduced walking speed and cadence, reduced step length, stride length, and swing phase, increased walking base width, stride time, step time, stance phase and double limb support phase with increased variability of step length, stride length, and stride time.

CONCLUSION

The consensus description provided here, clarifies the gait pattern associated with ataxic gait disturbance in a large cohort of participants. High quality research and reporting is needed to explore specific genetic diagnoses and identify biomarkers for disease progression in order to develop well-evidenced clinical guidelines and interventions for Cerebellar Ataxia.

Technology-Based Feedback and Its Efficacy in Improving Gait Parameters in Patients with Abnormal Gait: A Systematic Review

This systematic review synthesized and analyzed clinical findings related to the effectiveness of innovative technological feedback for tackling functional gait recovery. An electronic search of PUBMED, PEDro, WOS, CINAHL, and DIALNET was conducted from January 2011 to December 2016. The main inclusion criteria were: patients with modified or abnormal gait; application of technology-based feedback to deal with functional recovery of gait; any comparison between different kinds of feedback applied by means of technology, or any comparison between technological and non-technological feedback; and randomized controlled trials. Twenty papers were included. The populations were neurological patients (75%), orthopedic and healthy subjects. All participants were adults, bar one. Four studies used exoskeletons, 6 load platforms and 5 pressure sensors. The breakdown of the type of feedback used was as follows: 60% visual, 40% acoustic and 15% haptic. 55% used terminal feedback versus 65% simultaneous feedback. Prescriptive feedback was used in 60% of cases, while 50% used descriptive feedback. 62.5% and 58.33% of the trials showed a significant effect in improving step length and speed, respectively. Efficacy in improving other gait parameters such as balance or range of movement is observed in more than 75% of the studies with significant outcomes.

CONCLUSION

Treatments based on feedback using innovative technology in patients with abnormal gait are mostly effective in improving gait parameters and therefore useful for the functional recovery of patients. The most frequently highlighted types of feedback were immediate visual feedback followed by terminal and immediate acoustic feedback.