Fractal fluctuations in spatiotemporal variables when walking on a self-paced treadmill

This study investigated the fractal dynamic properties of stride time (ST), stride length (SL) and stride speed (SS) during walking on a self-paced treadmill (STM) in which the belt speed is automatically controlled by the walking speed. Twelve healthy young subjects participated in the study. The subjects walked at their preferred walking speed under four conditions: STM, STM with a metronome (STM+met), fixed-speed (conventional) treadmill (FTM), and FTM with a metronome (FTM+met). To compare the fractal dynamics between conditions, the mean, variability, and fractal dynamics of ST, SL, and SS were compared. Moreover, the relationship among the variables was examined under each walking condition using three types of surrogates. The mean values of all variables did not differ between the two treadmills, and the variability of all variables was generally larger for STM than for FTM. The use of a metronome resulted in a decrease in variability in ST and SS for all conditions. The fractal dynamic characteristics of SS were maintained with STM, in contrast to FTM, and only the fractal dynamic characteristics of ST disappeared when using a metronome. In addition, the fractal dynamic patterns of the cross-correlated surrogate results were identical to those of all variables for the two treadmills. In terms of the fractal dynamic properties, STM walking was generally closer to overground walking than FTM walking. Although further research is needed, the present results will be useful in research on gait fractal dynamics and rehabilitation.     

A simple,reliable method to determine the mean gait speed using heel markers on a treadmill

Gait speed is an essential parameter of gait analysis. Our study proposed a simple and accurate method to extract a mean gait speed during walking on a treadmill using only kinematic data from markers placed on the heels of the participants’ feet. This method provided an attractive, simple method that remains resistant to errors in treadmill calibration. In addition, this method required only two markers, since heel markers are essential to gait analysis, and the proposed method is robust enough to differentiate among various gait speeds (mean error <1%).     

A comparison of algorithms for body-worn sensor-based spatiotemporal gait parameters to the GAITRite electronic walkway

This study compares the performance of algorithms for body-worn sensors used with a spatiotemporal gait analysis platform to the GAITRite electronic walkway. The mean error in detection time (true error) for heel strike and toe-off was 33.9 ± 10.4 ms and 3.8 ± 28.7 ms, respectively. The ICC for temporal parameters step, stride, swing and stance time was found to be greater than 0.84, indicating good agreement. Similarly, for spatial gait parameters--stride length and velocity--the ICC was found to be greater than 0.88. Results show good to excellent concurrent validity in spatiotemporal gait parameters, at three different walking speeds (best agreement observed at normal walking speed). The reported algorithms for body-worn sensors are comparable to the GAITRite electronic walkway for measurement of spatiotemporal gait parameters in healthy subjects.     

The penguin waddling gait pattern has a more consistent step width than step length

Previous research has indicated that the sagittal plane gait dynamics of humans are more stable and less dependent on active neural control, while the frontal plane dynamics are less stable and require greater neural control. The higher neural demands of the frontal plane dynamics are reflected in a more variable step width than step length. Greater variability in the step width occurs because humans modulate their foot placement for each step to ensure stability and prevent falls. Compared to other terrestrial animals, penguins appear to have excessive amount of frontal plane motion in their gait that is characterized as waddling. If excessive frontal plane motion requires additional neural control and is associated with falls, it would seem that evolutionary pressures would have eliminated such locomotive strategies. Here we measured the step length and width variability to determine if waddling results in a less stable gait. Remarkably, the variability of the step width was less than the variability of the step length. These results are directly opposite of what has been reported for humans. Hence, our data indicate that waddling may be an effective strategy for ensuring stability in the frontal plane dynamics.     

Effects of general fatigue induced by incremental maximal exercise test on gait stability and variability of healthy young subjects

The purpose of this study was to determine whether general fatigue induced by incremental maximal exercise test (IMET) affects gait stability and variability in healthy subjects. Twenty-two young healthy male subjects walked in a treadmill at preferred walking speed for 4 min prior (PreT) the test, which was followed by three series of 4 min of walking with 4 min of rest among them. Gait variability was assessed using walk ratio (WR), calculated as step length normalized by step frequency, root mean square (RMS_ratio) of trunk acceleration, standard deviation of medial-lateral trunk acceleration between strides (VAR_ML), coefficient of variation of step frequency (SFCV), length (SLCV) and width (SWCV). Gait stability was assessed using margin of stability (MoS) and local dynamic stability (λ_s). VAR_ML, SFCV, SLCV and SWCV increased after the test indicating an increase in gait variability. MoS decreased and λ_s increased after the test, indicating a decrease in gait stability. All variables showed a trend to return to PreT values, but the 20-min post-test interval appears not to be enough for a complete recovery. The results showed that general fatigue induced by IMET alters negatively the gait, and an interval of at least 20 min should be considered for injury prevention in tasks with similar demands.     

IMU-based ambulatory walking speed estimation in constrained treadmill and overground walking

This study evaluated the performance of a walking speed estimation system based on using an inertial measurement unit (IMU), a combination of accelerometers and gyroscopes. The walking speed estimation algorithm segments the walking sequence into individual stride cycles (two steps) based on the inverted pendulum-like behaviour of the stance leg during walking and it integrates the angular velocity and linear accelerations of the shank to determine the displacement of each stride. The evaluation was performed in both treadmill and overground walking experiments with various constraints on walking speed, step length and step frequency to provide a relatively comprehensive assessment of the system. Promising results were obtained in providing accurate and consistent walking speed/step length estimation in different walking conditions. An overall percentage root mean squared error (%RMSE) of 4.2 and 4.0% was achieved in treadmill and overground walking experiments, respectively. With an increasing interest in understanding human walking biomechanics, the IMU-based ambulatory system could provide a useful walking speed/step length measurement/control tool for constrained walking studies.     

Gait variability magnitude but not structure is altered in essential tremor

Essential tremor (ET) is a common tremor disorder affecting postural/action tremor of the upper extremities and midline. Recent research revealed a cerebellar-like deficit during tandem gait in persons with ET, though spatiotemporal variability during normal gait in ET has been relatively ignored. The first purpose of this study was to investigate gait variability magnitude and structure in ET as compared to healthy older adults (HOA). To address this issue, 11 ET and 11 age-matched HOAs walked on a treadmill for 5 min at preferred walking speeds. HOAs walked for an additional minute while speed-matched to an ET participant. The second purpose was to describe the clinical correlates of gait variability in this population. To address this aim, 31 persons with ET walked on a treadmill for 5 min and completed the Fahn–Tolosa–Marin Tremor Rating Scale. Gait variability magnitude was derived by calculating coefficients of variation in stride length, stride time, step length, step time, and step width. Gait variability structure was derived using a detrended fluctuation analysis technique. At preferred walking speeds, ET participants walked significantly slower with significantly increased variability magnitude in all five spatiotemporal gait parameters. At speed-matched walking, ET participants exhibited significantly higher step width variability. Gait variability structure was not different between groups. We also observed that gait variability magnitude was predicted by severity of upper extremity and midline tremors. This study revealed that self-selected gait in ET is characterized by high variability that is associated with tremor severity in the upper extremity and midline.     

Walking speed changes in response to novel user-driven treadmill control

Implementing user-driven treadmill control in gait training programs for rehabilitation may be an effective means of enhancing motor learning and improving functional performance. This study aimed to determine the effect of a user-driven treadmill control scheme on walking speeds, anterior ground reaction forces (AGRF), and trailing limb angles (TLA) of healthy adults. Twenty-three participants completed a 10-m overground walking task to measure their overground self-selected (SS) walking speeds. Then, they walked at their SS and fastest comfortable walking speeds on an instrumented split-belt treadmill in its fixed speed and user-driven control modes. The user-driven treadmill controller combined inertial-force, gait parameter, and position based control to adjust the treadmill belt speed in real time. Walking speeds, peak AGRF, and TLA were compared among test conditions using paired t-tests (α = 0.05). Participants chose significantly faster SS and fast walking speeds in the user-driven mode than the fixed speed mode (p > 0.05). There was no significant difference between the overground SS walking speed and the SS speed from the user-driven trials (p < 0.05). Changes in AGRF and TLA were caused primarily by changes in walking speed, not the treadmill controller. Our findings show the user-driven treadmill controller allowed participants to select walking speeds faster than their chosen speeds on the fixed speed treadmill and similar to their overground speeds. Since user-driven treadmill walking increases cognitive activity and natural mobility, these results suggest user-driven treadmill control would be a beneficial addition to current gait training programs for rehabilitation.     

Dynamic gait stability of treadmill versus overground walking in young adults

Treadmill has been broadly used in laboratory and rehabilitation settings for the purpose of facilitating human locomotion analysis and gait training. The objective of this study was to determine whether dynamic gait stability differs or resembles between the two walking conditions (overground vs. treadmill) among young adults. Fifty-four healthy young adults (age: 23.9 ± 4.7 years) participated in this study. Each participant completed five trials of overground walking followed by five trials of treadmill walking at a self-selected speed while their full body kinematics were gathered by a motion capture system. The spatiotemporal gait parameters and dynamic gait stability were compared between the two walking conditions. The results revealed that participants adopted a “cautious gait” on the treadmill compared with over ground in response to the possible inherent challenges to balance imposed by treadmill walking. The cautious gait, which was achieved by walking slower with a shorter step length, less backward leaning trunk, shortened single stance phase, prolonged double stance phase, and more flatfoot landing, ensures the comparable dynamic stability between the two walking conditions. This study could provide insightful information about dynamic gait stability control during treadmill ambulation in young adults.     

Reliability and comparison of Kinect-based methods for estimating spatiotemporal gait parameters of healthy and post-stroke individuals

Different studies have analyzed the potential of the off-the-shelf Microsoft Kinect, in its different versions, to estimate spatiotemporal gait parameters as a portable markerless low-cost alternative to laboratory grade systems. However, variability in populations, measures, and methodologies prevents accurate comparison of the results. The objective of this study was to determine and compare the reliability of the existing Kinect-based methods to estimate spatiotemporal gait parameters in healthy and post-stroke adults. Forty-five healthy individuals and thirty-eight stroke survivors participated in this study. Participants walked five meters at a comfortable speed and their spatiotemporal gait parameters were estimated from the data retrieved by a Kinect v2, using the most common methods in the literature, and by visual inspection of the videotaped performance. Errors between both estimations were computed. For both healthy and post-stroke participants, highest accuracy was obtained when using the speed of the ankles to estimate gait speed (3.6–5.5 cm/s), stride length (2.5–5.5 cm), and stride time (about 45 ms), and when using the distance between the sacrum and the ankles and toes to estimate double support time (about 65 ms) and swing time (60–90 ms). Although the accuracy of these methods is limited, these measures could occasionally complement traditional tools.     

The effects of rhythmic sensory cues on the temporal dynamics of human gait

Walking is a complex, rhythmic task performed by the locomotor system. However, natural gait rhythms can be influenced by metronomic auditory stimuli, a phenomenon of particular interest in neurological rehabilitation. In this paper, we examined the effects of aural, visual and tactile rhythmic cues on the temporal dynamics associated with human gait. Data were collected from fifteen healthy adults in two sessions. Each session consisted of five 15-minute trials. In the first trial of each session, participants walked at their preferred walking speed. In subsequent trials, participants were asked to walk to a metronomic beat, provided through visually, aurally, tactile or all three cues (simultaneously and in sync), the pace of which was set to the preferred walking speed of the first trial. Using the collected data, we extracted several parameters including: gait speed, mean stride interval, stride interval variability, scaling exponent and maximum Lyapunov exponent. The extracted parameters showed that rhythmic sensory cues affect the temporal dynamics of human gait. The auditory rhythmic cue had the greatest influence on the gait parameters, while the visual cue had no statistically significant effect on the scaling exponent. These results demonstrate that visual rhythmic cues could be considered as an alternative cueing modality in rehabilitation without concern of adversely altering the statistical persistence of walking.     

Kinematic Validation of a Multi-Kinect v2 Instrumented 10-Meter Walkway for Quantitative Gait Assessments

Walking ability is frequently assessed with the 10-meter walking test (10MWT), which may be instrumented with multiple Kinect v2 sensors to complement the typical stopwatch-based time to walk 10 meters with quantitative gait information derived from Kinect’s 3D body point’s time series. The current study aimed to evaluate a multi-Kinect v2 set-up for quantitative gait assessments during the 10MWT against a gold-standard motion-registration system by determining between-systems agreement for body point’s time series, spatiotemporal gait parameters and the time to walk 10 meters. To this end, the 10MWT was conducted at comfortable and maximum walking speed, while 3D full-body kinematics was concurrently recorded with the multi-Kinect v2 set-up and the Optotrak motion-registration system (i.e., the gold standard). Between-systems agreement for body point’s time series was assessed with the intraclass correlation coefficient (ICC). Between-systems agreement was similarly determined for the gait parameters’ walking speed, cadence, step length, stride length, step width, step time, stride time (all obtained for the intermediate 6 meters) and the time to walk 10 meters, complemented by Bland-Altman’s bias and limits of agreement. Body point’s time series agreed well between the motion-registration systems, particularly so for body points in motion. For both comfortable and maximum walking speeds, the between-systems agreement for the time to walk 10 meters and all gait parameters except step width was high (ICC ≥ 0.888), with negligible biases and narrow limits of agreement. Hence, body point’s time series and gait parameters obtained with a multi-Kinect v2 set-up match well with those derived with a gold standard in 3D measurement accuracy. Future studies are recommended to test the clinical utility of the multi-Kinect v2 set-up to automate 10MWT assessments, thereby complementing the time to walk 10 meters with reliable spatiotemporal gait parameters obtained objectively in a quick, unobtrusive and patient-friendly manner.     

Two Independent Contributions to Step Variability during Over-Ground Human Walking

Human walking exhibits small variations in both step length and step width, some of which may be related to active balance control. Lateral balance is thought to require integrative sensorimotor control through adjustment of step width rather than length, contributing to greater variability in step width. Here we propose that step length variations are largely explained by the typical human preference for step length to increase with walking speed, which itself normally exhibits some slow and spontaneous fluctuation. In contrast, step width variations should have little relation to speed if they are produced more for lateral balance. As a test, we examined hundreds of overground walking steps by healthy young adults (N = 14, age < 40 yrs.). We found that slow fluctuations in self-selected walking speed (2.3% coefficient of variation) could explain most of the variance in step length (59%, P < 0.01). The residual variability not explained by speed was small (1.5% coefficient of variation), suggesting that step length is actually quite precise if not for the slow speed fluctuations. Step width varied over faster time scales and was independent of speed fluctuations, with variance 4.3 times greater than that for step length (P < 0.01) after accounting for the speed effect. That difference was further magnified by walking with eyes closed, which appears detrimental to control of lateral balance. Humans appear to modulate fore-aft foot placement in precise accordance with slow fluctuations in walking speed, whereas the variability of lateral foot placement appears more closely related to balance. Step variability is separable in both direction and time scale into balance- and speed-related components. The separation of factors not related to balance may reveal which aspects of walking are most critical for the nervous system to control.     

Energy cost of balance control during walking decreases with external stabilizer stiffness independent of walking speed

Human walking requires active neuromuscular control to ensure stability in the lateral direction, which inflicts a certain metabolic load. The magnitude of this metabolic load has previously been investigated by means of passive external lateral stabilization via spring-like cords. In the present study, we applied this method to test two hypotheses: (1) the effect of external stabilization on energy cost depends on the stiffness of the stabilizing springs, and (2) the energy cost for balance control, and consequently the effect of external stabilization on energy cost, depends on walking speed. Fourteen healthy young adults walked on a motor driven treadmill without stabilization and with stabilization with four different spring stiffnesses (between 760 and 1820 N m⁻¹) at three walking speeds (70%, 100%, and 130% of preferred speed). Energy cost was calculated from breath-by-breath oxygen consumption. Gait parameters (mean and variability of step width and stride length, and variability of trunk accelerations) were calculated from kinematic data. On average external stabilization led to a decrease in energy cost of 6% (p<0.005) as well as a decrease in step width (24%; p<0.001), step width variability (41%; p<0.001) and variability of medio-lateral trunk acceleration (12.5%; p<0.005). Increasing stabilizer stiffness increased the effects on both energy cost and medio-lateral gait parameters up to a stiffness of 1260 N m⁻¹. Contrary to expectations, the effect of stabilization was independent of walking speed (p=0.111). These results show that active lateral stabilization during walking involves an energetic cost, which is independent of walking speed.     

Two-dimensional video-based analysis of human gait using pose estimation

Human gait analysis is often conducted in clinical and basic research, but many common approaches (e.g., three-dimensional motion capture, wearables) are expensive, immobile, data-limited, and require expertise. Recent advances in video-based pose estimation suggest potential for gait analysis using two-dimensional video collected from readily accessible devices (e.g., smartphones). To date, several studies have extracted features of human gait using markerless pose estimation. However, we currently lack evaluation of video-based approaches using a dataset of human gait for a wide range of gait parameters on a stride-by-stride basis and a workflow for performing gait analysis from video. Here, we compared spatiotemporal and sagittal kinematic gait parameters measured with OpenPose (open-source video-based human pose estimation) against simultaneously recorded three-dimensional motion capture from overground walking of healthy adults. When assessing all individual steps in the walking bouts, we observed mean absolute errors between motion capture and OpenPose of 0.02 s for temporal gait parameters (i.e., step time, stance time, swing time and double support time) and 0.049 m for step lengths. Accuracy improved when spatiotemporal gait parameters were calculated as individual participant mean values: mean absolute error was 0.01 s for temporal gait parameters and 0.018 m for step lengths. The greatest difference in gait speed between motion capture and OpenPose was less than 0.10 m s⁻¹. Mean absolute error of sagittal plane hip, knee and ankle angles between motion capture and OpenPose were 4.0°, 5.6° and 7.4°. Our analysis workflow is freely available, involves minimal user input, and does not require prior gait analysis expertise. Finally, we offer suggestions and considerations for future applications of pose estimation for human gait analysis.     

Concurrent validity of the Microsoft Kinect for assessment of spatiotemporal gait variables

Spatiotemporal characteristics of gait such as step time and length are often associated with overall physical function in clinical populations, but can be difficult, time consuming and obtrusive to measure. This study assessed the concurrent validity of overground walking spatiotemporal data recorded using a criterion reference – a marker-based three-dimensional motion analysis (3DMA) system – and a low-cost, markerless alternative, the automated skeleton tracking output from the Microsoft Kinect™ (Kinect). Twenty-one healthy adults performed normal walking trials while being monitored using both systems. The outcome measures of gait speed, step length and time, stride length and time and peak foot swing velocity were derived using supervised automated analysis. To assess the agreement between the Kinect and 3DMA devices, Bland–Altman 95% bias and limits of agreement, percentage error, relative agreement (Pearson's correlation coefficients: r) overall agreement (concordance correlation coefficients: r_c) and landmark location linearity as a function of distance from the sensor were determined. Gait speed, step length and stride length from the two devices possessed excellent agreement (r and r_c values >0.90). Foot swing velocity possessed excellent relative (r=0.93) but only modest overall (r_c=0.54) agreement. Step time (r=0.82 and r_c=0.23) and stride time (r=0.69 and r_c=0.14) possessed excellent and modest relative agreement respectively but poor overall agreement. Landmark location linearity was excellent (R²=0.991). This widely available, low-cost and portable system could provide clinicians with significant advantages for assessing some spatiotemporal gait parameters. However, caution must be taken when choosing outcome variables as some commonly reported variables cannot be accurately measured.     

Reliability and Minimum Detectable Change of Temporal-Spatial,Kinematic, and Dynamic Stability Measures during Perturbed Gait

Temporal-spatial, kinematic variability, and dynamic stability measures collected during perturbation-based assessment paradigms are often used to identify dysfunction associated with gait instability. However, it remains unclear which measures are most reliable for detecting and tracking responses to perturbations. This study systematically determined the between-session reliability and minimum detectable change values of temporal-spatial, kinematic variability, and dynamic stability measures during three types of perturbed gait. Twenty young healthy adults completed two identical testing sessions two weeks apart, comprised of an unperturbed and three perturbed (cognitive, physical, and visual) walking conditions in a virtual reality environment. Within each session, perturbation responses were compared to unperturbed walking using paired t-tests. Between-session reliability and minimum detectable change values were also calculated for each measure and condition. All temporal-spatial, kinematic variability and dynamic stability measures demonstrated fair to excellent between-session reliability. Minimal detectable change values, normalized to mean values ranged from 1–50%. Step width mean and variability measures demonstrated the greatest response to perturbations with excellent between-session reliability and low minimum detectable change values. Orbital stability measures demonstrated specificity to perturbation direction and sensitivity with excellent between-session reliability and low minimum detectable change values. We observed substantially greater between-session reliability and lower minimum detectable change values for local stability measures than previously described which may be the result of averaging across trials within a session and using velocity versus acceleration data for reconstruction of state spaces. Across all perturbation types, temporal-spatial, orbital and local measures were the most reliable measures with the lowest minimum detectable change values, supporting their use for tracking changes over multiple testing sessions. The between-session reliability and minimum detectable change values reported here provide an objective means for interpreting changes in temporal-spatial, kinematic variability, and dynamic stability measures during perturbed walking which may assist in identifying instability.     

Step-to-Step Variability in Treadmill Walking: Influence of Rhythmic Auditory Cueing

While walking, human beings continuously adjust step length (SpL), step time (SpT), step speed (SpS = SpL/SpT) and step width (SpW) by integrating both feedforward and feedback mechanisms. These motor control processes result in correlations of gait parameters between consecutive strides (statistical persistence). Constraining gait with a speed cue (treadmill) and/or a rhythmic auditory cue (metronome), modifies the statistical persistence to anti-persistence. The objective was to analyze whether the combined effect of treadmill and rhythmic auditory cueing (RAC) modified not only statistical persistence, but also fluctuation magnitude (standard deviation, SD), and stationarity of SpL, SpT, SpS and SpW. Twenty healthy subjects performed 6×5 min. walking tests at various imposed speeds on a treadmill instrumented with foot-pressure sensors. Freely-chosen walking cadences were assessed during the first three trials, and then imposed accordingly in the last trials with a metronome. Fluctuation magnitude (SD) of SpT, SpL, SpS and SpW was assessed, as well as NonStationarity Index (NSI), which estimates the dispersion of local means in the times series (SD of 20 local means over 10 steps). No effect of RAC on fluctuation magnitude (SD) was observed. SpW was not modified by RAC, what is likely the evidence that lateral foot placement is separately regulated. Stationarity (NSI) was modified by RAC in the same manner as persistent pattern: Treadmill induced low NSI in the time series of SpS, and high NSI in SpT and SpL. On the contrary, SpT, SpL and SpS exhibited low NSI under RAC condition. We used relatively short sample of consecutive strides (100) as compared to the usual number of strides required to analyze fluctuation dynamics (200 to 1000 strides). Therefore, the responsiveness of stationarity measure (NSI) to cued walking opens the perspective to perform short walking tests that would be adapted to patients with a reduced gait perimeter.