Association between stride time fractality and gait adaptability during unperturbed and asymmetric walking

Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running

Introduction: The seemingly periodic human gait exhibits stride-to-stride variations as it adapts to the changing task constraints. The optimal movement variability hypothesis (OMVH) states that healthy stride-to-stride variations exhibit "fractality"-a specific temporal structure in consecutive strides that are ordered, stable but also variable, and adaptable. Previous research has primarily focused on a single fractality measure, "monofractality." However, this measure can vary across time; strideto-stride variations can show "multifractality." Greater multifractality in stride-tostride variations would highlight the ability to tune and adjust movements more. Methods: We investigated monofractality and multifractality in a cohort of eight healthy adults during self-paced walking and running trials, both on a treadmill and overground. Footfall data were collected through force-sensitive sensors positioned on their heels and feet. We examined the effects of self-paced walking vs. running and treadmill vs. overground locomotion on the measure of monofractality, α-DFA, in addition to the multifractal spectrum width, W, and the asymmetry in the multifractal spectrum, WAsym, of stride interval time series. Results: While the α-DFA was larger than 0.50 for almost all conditions, α-DFA was higher in running and locomoting overground than walking and locomoting on a treadmill. Similarly, W was greater while locomoting overground than on a treadmill, but an opposite trend indicated that W was greater in walking than running. Larger WAsym values in the negative direction suggest that walking exhibits more variation in the persistence of shorter stride intervals than running. However, the ability to tune and adjust movements does not differ between treadmill and overground, although both exhibit more variation in the persistence of shorter stride intervals. Discussion: Hence, greater heterogeneity in shorter than longer stride intervals contributed to greater multifractality in walking compared to running, indicated by larger negative WAsym values. Our results highlight the need to incorporate multifractal methods to test the predictions of the OMVH.

An Exploratory Study of Walking, Listening, and Remembering in Younger and Middle-Aged Adults

PURPOSE

The purpose of this study was to assess how needing to listen and remember information while walking affects speech perception, memory task performance, and gait in younger and middle-aged adults.

METHOD

Four gait parameters (stride duration, step variability, whole-body center of mass acceleration, and mediolateral head acceleration) were measured when younger and middle-aged participants stood or walked on a treadmill while they simultaneously completed a speech-on-speech perception task and a preload memory task, singly and in combination.

RESULTS

Speech perception was significantly poorer for middle-aged than for younger participants. Performance on the speech perception measure did not differ significantly between walking and standing for either group of participants, but the additional cognitive load of the memory task reduced performance on the speech perception task. Memory task performance was significantly poorer when combined with the speech perception task than when measured in isolation for both participant groups, but no further declines were noted when participants were also walking. Mediolateral head acceleration, which has been linked to loss of balance, was significantly greater during multitask trials, as compared to when participants were only walking without being required to listen or remember. Post hoc analysis showed that dual- and multitask influences on mediolateral head acceleration were more prominent for middle-aged than for younger participants. Stride duration was longer in the multitask condition than when participants were only walking.

CONCLUSIONS

Results of this exploratory study indicate that gait may be impacted when individuals (both younger and middle-aged) are listening and remembering while walking. Data also substantiate prior findings of early age-related declines in the perception of speech in the presence of understandable speech maskers.

Integrating Motor Variability Evaluation Into Movement System Assessment

Common assessment tools for determining therapeutic success in rehabilitation typically focus on task-based outcomes. Task-based outcomes provide some understanding of the individual's functional ability and motor recovery; however, these clinical outcomes may have limited translation to a patient's functional ability in the real world. Limitations arise because (1) the focus on task-based outcome assessment often disregards the complexity of motor behavior, including motor variability, and (2) mobility in highly variable real-world environments requires movement adaptability that is made possible by motor variability. This Perspective argues that incorporating motor variability measures that reflect movement adaptability into routine clinical assessment would enable therapists to better evaluate progress toward optimal and safe real-world mobility. The challenges and opportunities associated with incorporating variability-based assessment of pathological movements are also discussed. This Perspective also indicates that the field of rehabilitation needs to leverage technology to advance the understanding of motor variability and its impact on an individual's ability to optimize movement.

IMPACT

This Perspective contends that traditional therapeutic assessments do not adequately evaluate the ability of individuals to adapt their movements to the challenges faced when negotiating the dynamic environments encountered during daily life. Assessment of motor variability derived during movement execution can address this issue and provide better insight into a patient's movement stability and maneuverability in the real world. Creating such a shift in motor system assessment would advance understanding of rehabilitative approaches to motor system recovery and intervention.

Considerations for Applying Entropy Methods to Temporally Correlated Stochastic Datasets

The goal of this paper is to highlight considerations and provide recommendations for analytical issues that arise when applying entropy methods, specifically Sample Entropy (SampEn), to temporally correlated stochastic datasets, which are representative of a broad range of biomechanical and physiological variables. To simulate a variety of processes encountered in biomechanical applications, autoregressive fractionally integrated moving averaged (ARFIMA) models were used to produce temporally correlated data spanning the fractional Gaussian noise/fractional Brownian motion model. We then applied ARFIMA modeling and SampEn to the datasets to quantify the temporal correlations and regularity of the simulated datasets. We demonstrate the use of ARFIMA modeling for estimating temporal correlation properties and classifying stochastic datasets as stationary or nonstationary. We then leverage ARFIMA modeling to improve the effectiveness of data cleaning procedures and mitigate the influence of outliers on SampEn estimates. We also emphasize the limitations of SampEn to distinguish among stochastic datasets and suggest the use of complementary measures to better characterize the dynamics of biomechanical variables. Finally, we demonstrate that parameter normalization is not an effective procedure for increasing the interoperability of SampEn estimates, at least not for entirely stochastic datasets.

The Foot Fault Scoring System to Assess Skilled Walking in Rodents: A Reliability Study

The foot fault scoring system of the ladder rung walking test (LRWT) is used to assess skilled walking in rodents. However, the reliability of the LRWT foot fault score has not been properly addressed. This study was designed to address this issue. Two independent and blinded raters analyzed 20 rats and 20 mice videos. Each video was analyzed twice by the same rater (80 analyses per rater). The intraclass correlation coefficient (ICC) and the Kappa coefficient were employed to check the accuracy of agreement and reliability in the intra- and inter-rater analyses of the LRWT outcomes. Excellent intra- and inter-rater agreements were found for the forelimb, hindlimb, and both limbs combined in rats and mice. The agreement level was also excellent for total crossing time, total time stopped, and the number of stops during the walking path. Rating individual scores in the foot fault score system (0–6) ranged from satisfactory to excellent, in terms of the intraclass correlation indexes. Moreover, we showed that experienced and inexperienced raters can obtain reliable results if supervised training is provided. We concluded that the LRWT is a reliable and useful tool to study skilled walking in rodents and can help researchers address walking-related neurobiological questions.

Diagnosing gait disorders based on angular variations of knee and ankle joints utilizing a developed wearable motion sensor

Here, a sensory motion system is developed to diagnose gait disorders using the estimation of angular variations in the knee and ankle joints. The sensory system includes two transmitter sensors and a central node, where each transmitter comprises three sensors of accelerometer, gyroscopes, and magnetometer to estimate the angular movements in the ankle and knee joints. By using a proposed filter, the angular variation is estimated in a personal computer employing the raw data of the motion sensors that are sent by the central node. The obtained results of the presented filter in comparison to an actual reference illustrate that the root mean square error is less than 1.01, 1.34, and 1.61 degrees, respectively, for the angles of ϕ and θ and ψ that illustrate an improvement of 40% than the previous work. Moreover, a quantity value is defined based on the correlation between knee and ankle angles that show the amount of correctness in gating. Thus, the proposed system can be utilized for people who suffer problems in gait and help them to improve their movements.

Gait Stability Measurement by Using Average Entropy

Gait stability has been measured by using many entropy-based methods. However, the relation between the entropy values and gait stability is worth further investigation. A research reported that average entropy (AE), a measure of disorder, could measure the static standing postural stability better than multiscale entropy and entropy of entropy (EoE), two measures of complexity. This study tested the validity of AE in gait stability measurement from the viewpoint of the disorder. For comparison, another five disorders, the EoE, and two traditional metrics methods were, respectively, used to measure the degrees of disorder and complexity of 10 step interval (SPI) and 79 stride interval (SI) time series, individually. As a result, every one of the 10 participants exhibited a relatively high AE value of the SPI when walking with eyes closed and a relatively low AE value when walking with eyes open. Most of the AE values of the SI of the 53 diseased subjects were greater than those of the 26 healthy subjects. A maximal overall accuracy of AE in differentiating the healthy from the diseased was 91.1%. Similar features also exists on those 5 disorder measurements but do not exist on the EoE values. Nevertheless, the EoE versus AE plot of the SI also exhibits an inverted U relation, consistent with the hypothesis for physiologic signals.

Sports Injury Forecasting and Complexity: A Synergetic Approach

The understanding that sports injury is the result of the interaction among many factors and that specific profiles could increase the risk of the occurrence of a given injury was a significant step in establishing programs for injury prevention. However, injury forecasting is far from being attained. To be able to estimate future states of a complex system (forecasting), it is necessary to understand its nature and comply with the methods usually used to analyze such a system. In this sense, sports injury forecasting must implement the concepts and tools used to study the behavior of self-organizing systems, since it is by self-organizing that systems (i.e., athletes) evolve and adapt (or not) to a constantly changing environment. Instead of concentrating on the identification of factors related to the injury occurrence (i.e., risk factors), a complex systems approach looks for the high-order variables (order parameters) that describe the macroscopic dynamic behavior of the athlete. The time evolution of this order parameter informs on the state of the athlete and may warn about upcoming events, such as injury. In this article, we describe the fundamental concepts related to complexity based on physical principles of self-organization and the consequence of accepting sports injury as a complex phenomenon. In the end, we will present the four steps necessary to formulate a synergetics approach based on self-organization and phase transition to sports injuries. Future studies based on this experimental paradigm may help sports professionals to forecast sports injuries occurrence.

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.

Test-retest reliability of multiscale fractal dimension measurements of plantar pressure maps during dynamic tasks

The tools used to evaluate foot types are divergent since they adopt classic linear analyzes, based on anthropometric or image measurements, which do not dynamically contemplate the variability of foot shape. The use of newer techniques such as multiscale fractal dimension (MFD) may be a key to this type of problem. However, for these measures to be used safely and consistently, it is essential to evaluate their reliability. The aim of this study was to evaluate the test-retest reliability of MFD measurements of adult plantar pressure maps during gait, as well as the standard error of measurement (SEM), and minimal detectable change (MDC₉₀). Seventy-two subjects were included in the test-retest, with a one week interval. The plantar pressure maps were constructed using a pressure platform. The data were processed in a routine for extracting the MFD curve measurements (maximum and integral values). The Intraclass Correlation Coefficient results (ICC_3,k) were excellent for both measurements (maximum value 0.96, 95% confidence interval [0.93-0.97], and integral 0.95 [0.92-0.97]) with low SEM and MDC₉₀ values below 10% of the mean. The application of MFD to the plantar pressure data generated by the pressure platform is reliable and could allow exploration of the complexity of foot shapes, enabling their classification.

Predicting aperture crossing behavior from within-trial metrics of motor control reliability

Actors utilize intrinsically scaled information about their geometric and dynamic properties when perceiving their ability to pass through openings. Research about dynamic factors of affordance perception have shown that the reliability of a given movement, or the precision of one's motor control for that movement, increase the buffer space used when interacting with the environment. While previous work has assessed motor control reliability as a person-level variable (i.e., behavior is aggregated across many trials), the current study assessed how characteristics of motor control and movement reliability within a single trial impact real-time action strategies for passing through apertures. Participants walked 5 m and then passed through apertures of various widths while their motions were tracked. For each trial, we collected walking time-series data, then calculated the magnitude and complexity of the lateral sway. Assessing two behavioral measures of the buffer, we found that trial-level metrics of motor control reliability, in addition to the person-level metrics previously studied, significantly predicted the buffer on each trial. This study supports previous claims that actors pick up real-time information about their dynamic capabilities in order to perceive and act within their environment. Further, the study recommends that future affordance research consider trial-level movement data, including nonlinear analyses that inform the pattern and structure of motor control reliability.

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.

Comparable Stride Time Fractal Dynamics and Gait Adaptability in Active Young and Older Adults Under Normal and Asymmetric Walking

Previous research indicates the correlation structure of gait parameters (i.e., fractal dynamics) decreases with age. This decrease is suggested to reflect a reduced capacity for locomotor adaptation in older adults. The purpose of this study was to investigate potential differences between physical activity-matched young and older adults’ fractal dynamics and gait adaptability during unperturbed and asymmetric walking, and to determine if fractal dynamics predict adaptive capacity. Fifteen young (28.9 ± 5.6 years, nine women) and 15 older (64.7 ± 2.7, nine women) adults with similar habitual physical activity levels walked at preferred speed, half of preferred speed, and asymmetrically whereby their dominant and non-dominant legs moved at preferred and half-preferred speed, respectively. Fractal correlations (scaling exponent α) of stride times were assessed through detrended fluctuation analysis, and gait adaptation to asymmetric walking on the basis of lower limb relative phase. Both cohorts displayed similar fractal dynamics at preferred speed and asymmetric walking, while older adults exhibited greater α during slow walking. Both groups exhibited comparable gait adaptation to split-belt walking based on analysis of lower limb relative phase. Fractal dynamics during preferred speed and asymmetric walking was moderately associated with gait adaptation in the young and older adult cohorts, respectively. In these activity-matched groups, there were no age-based reductions in fractal dynamics or gait adaptation, and fractal scaling α was moderately associated with gait adaptation. These findings suggest that stride time fractal dynamics and gait adaptation may be preserved in older adults who habitually perform moderate intensity physical activity.