Economy, Movement Dynamics, and Muscle Activity of Human Walking at Different Speeds

Are clinical tests and biomechanical measures of gait stability able to differentiate fallers from non-fallers in hereditary spastic paraplegia?

INTRODUCTION

Balance and gait impairments are common in people with hereditary spastic paraplegia (HSP) and often result in falls. Measures that identify patients at risk of falling are clinically relevant, but relatively unexplored in HSP. Here, we evaluated the potential of different balance and gait constructs to (1) identify differences between healthy controls and people with HSP and (2) discriminate between fallers and non-fallers with HSP.

METHODS

We included 33 people with pure-HSP and 15 healthy controls. We assessed balance confidence (six-item Activities-specific Balance Confidence scale), clinical balance capacity (Mini-Balance Evaluation Systems Test) and gait capacity (ten-meter Walk Test). Biomechanical measures included spatiotemporal gait variability, mediolateral Margin of Stability (MoS), Foot Placement Deviation (FPD), and Local Divergence Exponents (LDEs) of trunk and pelvis, derived from treadmill-walking at comfortable and fixed gait speeds. People with HSP logged their falls during a fifteen-week period and were categorized as 'faller' (≥1 fall) or 'non-faller'.

RESULTS

People with HSP had significantly lower balance confidence, balance capacity, and gait capacity compared to age-matched controls. People with HSP also showed reduced gait stability, reflected by increased spatiotemporal gait variability, FPD, and LDEs of trunk and pelvis. Overall, 44 % of people with HSP were categorized as 'faller'. Balance confidence (AUC:0.84) and balance capacity (AUC:0.75) discriminated fallers from non-fallers, whereas none of the biomechanical measures significantly differed.

CONCLUSION

Balance confidence, clinical balance and gait capacity, and biomechanical measures are affected in HSP, but clinical measures showed potential to differentiate fallers from non-fallers in people with HSP.

Causal interactions and dynamic stability between limbs while walking with imposed leg constraints

Aim

To investigate the dynamics of the motor control system during walking by examining the complexity, stability, and causal relationships of leg motions. Specifically, the study focuses on gait under both bilateral and unilateral constraints induced by a passive exoskeleton designed to replicate gastrocnemius contractures.

Methods

Kinematic data was collected as 10 healthy participants walked at a self-selected speed. A new Complexity-Instability Index (CII) of the leg motions was defined as a function of the Correlation Dimension and the Largest Lyapunov Exponent. Causal interactions between the leg motions are explored using Convergent Cross Mapping.

Results

Normal walking is characterized by a high mutual drive of each leg to the other, where CII is lowest for both legs (complexity of each leg motion is low and stability high). The effect of the bilateral emulated contractures is a reduced drive of each leg to the other and an increased CII for both legs. With unilateral emulated contracture, the mechanically constrained leg strongly drives the unconstrained leg, and CII was significantly higher for the constrained leg compared to normal walking.

Conclusion

Redundancy in limb motions is used to support causal interactions, reducing complexity and increasing stability in our leg dynamics during walking. The role of redundancy is to allow adaptability above being able to satisfy the overall biomechanical problem; and to allow the system to interact optimally. From an applied perspective, important characteristics of functional movement patterns might be captured by these nonlinear and causal variables, as well as the biomechanical aspects typically studied.

Load increases IMU signal attenuation per step but reduces IMU signal attenuation per kilometre

BACKGROUND

Despite deleterious biomechanics associated with injury, particularly as it pertains to load carriage, there is limited research on the association between physical demands and variables captured with wearable sensors. While inertial measurement units (IMUs) can be used as surrogate measures of ground reaction force (GRF) variables, it is unclear if these data are sensitive to military-specific task demands.

RESEARCH QUESTION

Can wearable sensors characterise physical load and demands placed on individuals in different load, speed and grade conditions?

METHODS

Data were collected on 20 individuals who were self-reportedly free from current injury, recreationally active, and capable of donning 23 kg in the form of a weighted vest. Each participant walked and ran on flat, uphill (+6 %) and downhill (-6 %) without and with load (23 kg). Data were collected synchronously from optical motion capture (OMC) and IMUs placed on the distal limb and the pelvis. Data from an 8-second window was used to generate a participant-based mean of OMC and IMU variables of interest. Repeated Measures ANOVA was used to measure main and interaction effects of load, speed, and grade. Simple linear regression was used to elucidate a relationship between OMC measures and estimated metabolic cost (EMC) to IMU measures.

RESULTS

Load reduces foot and pelvic accelerations (p<0.001) but elevate signal attenuation per step (p=0.044). Conversely, attenuation per kilometre is lowered with the addition of load (p=0.017). Uphill had the lowest attenuation per step (p=0.003) and kilometre (p≤0.033) in walking, while downhill had the greatest attenuation per step (p≤0.002) and per kilometre (p≤0.004). Attenuation measures are inconsistently moderately related to limb negative work (R≤0.57). EMC is moderately positively related to unloaded running (R≥0.39), and moderately negatively related to walking with and without load (R≤-0.52).

SIGNIFICANCE

While load reduces peak accelerations at both the pelvis and foot. However, it may increase demand on the lower extremity to attenuate the signal between the two sensors with each step, while attenuation over time reduces with load.

The nature of gait biomechanics changes with walking speed increase in patients with anterior cruciate ligament injury

BACKGROUND

This study on gait biomechanics is based on a functional test (FT) performed at free and fast walking speeds.

OBJECTIVE

We investigated the pattern of changes in gait biomechanical parameters and the knee function in patients after anterior cruciate ligament (ACL) injury or its reconstruction.

METHODS

The study included 51 patients (33 males, 18 females) with a confirmed recent or old history of ACL tear, before or after reconstruction (26 patients). Mocap data was obtained using an inertial system. All patients were divided into three groups: 41 patients with physiological response (compensation), 6 patients with signs of decompensation, and 4 non-assessable patients.

RESULTS

Increase in gait speed was associated with decrease in the walking cycle duration, stance and double support phases. In the compensation group, the physiological response of the knee was manifested in increased amplitudes. In the decompensation group, the amplitudes remained unchanged or decreased. In the compensation group, there were increases in the symmetrical muscle activity. The decompensation group was characterized by electromyography asymmetry.

CONCLUSION

The observed universal physiological mechanism limiting the load on the damaged joint can be used for accurate assessment of the knee functional state in various periods of rehabilitation.

Opioid-Induced Reductions in Gait Variability in Healthy Volunteers and Individuals with Knee Osteoarthritis

OBJECTIVE

To investigate differences in gait variability induced by two different single-dose opioid formulations and an inert placebo in healthy volunteers and knee osteoarthritis patients.

DESIGN

Experimental, randomized, double-blinded, crossover study of inert placebo (calcium tablets), 50 mg of tapentadol, and 100 mg of tramadol.

SETTING

Laboratory setting.

SUBJECTS

Healthy volunteers and knee osteoarthritis patients.

METHODS

At three visits, separated by seven days, one tablet was administered per visit according to the randomization code. At each visit, a baseline measurement was done before tablet administration, after which hourly measurements were performed for six hours, yielding a total of seven measurements per visit. Gait variability was measured by three-dimensional gait analysis, recorded during six minutes of continuous treadmill walking at self-selected speed. One hundred seventy gait cycles were identified from detection of clear events of the knee joint angle trajectories. Gait variability was assessed as average standard deviations over a gait cycle of the sacrum displacements and accelerations; sagittal plane ankle, knee, and hip joint angles; step widths; and stride times.

RESULTS

Twenty-four opioid-naïve and neurologically intact participants (12 healthy volunteers and 12 knee osteoarthritis patients) were included and completed the experiment. Tapentadol reduced the variability of sacrum displacements and accelerations compared with placebo and tramadol. There were no differences between experimental conditions regarding the variability in lower-extremity joint angle variability, step widths, or stride times.

CONCLUSIONS

In opioid-naïve and neurologically intact individuals, tapentadol seems to reduce movement variability during treadmill walking, compared with placebo and tramadol. This can be interpreted as a loss of adaptability that might increase the risk of falling if the system is perturbed.

To walk or to run - a question of movement attractor stability

During locomotion, humans change gait mode between walking and running as locomotion speed is either increased or decreased. Dynamical systems theory predicts that the self-organization of coordinated motor behaviors dictates the transition from one distinct stable attractor behavior to another distinct attractor behavior (e.g. walk to run or vice versa) as the speed is changed. To evaluate this prediction, the present study investigated the attractor stability of walking and running across a range of speeds evoking both self-selected gait mode and non-self-selected gait mode. Eleven subjects completed treadmill walking for 3 min at 0.89, 1.12, 1.34, 1.56, 1.79, 2.01, 2.24 and 2.46 m s-1 and running for 3 min at 1.79, 2.01, 2.24, 2.46, 2.68, 2.91, 3.13 and 3.35 m s-1 in randomized order while lower limb joint angles and sacrum displacements was recorded. Attractor stability was quantified by continuous relative phase and deviation phase of lower limb segment angles, and the largest Lyapunov exponent, correlation dimension and movement variability of the sacrum marker displacement and the hip, knee and ankle joint angles. Lower limb attractor stability during walking was maximized at speeds close to the self-selected preferred walking speed and increased during running as speed was increased. Furthermore, lower limb attractor stability was highest at a particular gait mode closest to the corresponding preferred speed, in support of the prediction of dynamical systems theory. This was not the case for the sacrum displacement attractor, suggesting that lower limb attractor behavior provides a more appropriate order parameter compared with sacrum displacement.

Filtering affects the calculation of the largest Lyapunov exponent

The calculation of the largest Lyapunov exponent (LyE) requires the reconstruction of the time series in an N-dimensional state space. For this, the time delay (Tau) and embedding dimension (EmD) are estimated using the Average Mutual Information and False Nearest Neighbor algorithms. However, the estimation of these variables (LyE, Tau, EmD) could be compromised by prior filtering of the time series evaluated. Therefore, we investigated the effect of filtering kinematic marker data on the calculation of Tau, EmD and LyE using several different computational codes. Kinematic marker data were recorded from 37 subjects during treadmill walking and filtered using a low pass digital filter with a range of cut-off frequencies (23.5-2Hz). Subsequently, the Tau, EmD and LyE were calculated from all cut-off frequencies. Our results demonstrated that the level of filtering affected the outcome of the Tau, EmD and LyE calculations for all computational codes used. However, there was a more consistent outcome for cut-off frequencies above 10 Hz which corresponded to the optimal cut-off frequency that could be used with this data. This suggested that kinematic data should remain unfiltered or filtered conservatively before calculating Tau, EmD and LyE.

Multi-objective control in human walking: insight gained through simultaneous degradation of energetic and motor regulation systems

Minimization of metabolic energy is considered a fundamental principle of human locomotion, as demonstrated by an alignment between the preferred walking speed (PWS) and the speed incurring the lowest metabolic cost of transport. We aimed to (i) simultaneously disrupt metabolic cost and an alternate acute task requirement, namely speed error regulation, and (ii) assess whether the PWS could be explained on the basis of either optimality criterion in this new performance and energetic landscape. Healthy adults (N = 21) walked on an instrumented treadmill under normal conditions and, while negotiating a continuous gait perturbation, imposed leg-length asymmetry. Oxygen consumption, motion capture data and ground reaction forces were continuously recorded for each condition at speeds ranging from 0.6 to 1.8 m s^-1, including the PWS. Both metabolic and speed regulation measures were disrupted by the perturbation (p < 0.05). Perturbed PWS selection did not exhibit energetic prioritization (although we find some indication of energy minimization after motor adaptation). Similarly, PWS selection did not support prioritization of speed error regulation, which was found to be independent of speed in both conditions. It appears that, during acute exposure to a mechanical gait perturbation of imposed leg-length asymmetry, humans minimize neither energetic cost nor speed regulation errors. Despite the abundance of evidence pointing to energy minimization during normal, steady-state gait, this may not extend acutely to perturbed gait. Understanding how the nervous system acutely controls gait perturbations requires further research that embraces multi-objective control paradigms.

Neuromuscular organisation and robustness of postural control in the presence of perturbations

Perturbation-based exercise interventions challenge balance and improve reactive motor control. Our purpose was to investigate the modular organisation during a standing balance task in both stable and unstable conditions to provide new insights into the neuromuscular control mechanisms needed to cope with perturbations. Fifteen participants performed 54 cycles of a specific task (i.e. pass from a double- to a single-leg standing) on stable ground and an unstable oscillating platform (Posturomed). Muscle synergies were extracted from the electromyographic activity of thirteen lower limb muscles. The maximum Lyapunov exponents of different body segments were calculated using kinematic data. We found two synergies functionally associated with the single- and double-leg stance in both stable and unstable conditions. Nonetheless, in the unstable condition participants needed an extra muscle synergy also functionally related to the single stance. Although a simple organisation of the neuromuscular system was sufficient to maintain the postural control in both conditions, the increased challenge in the oscillating platform was solved by adding one extra synergy. The addition of a new synergy with complementary function highlighted an increased motor output's robustness (i.e. ability to cope with errors) in the presence of perturbations.

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.

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

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

Day-to-Day Reliability of Nonlinear Methods to Assess Walking Dynamics

The present study investigated the day-to-day reliability (quantified by the absolute and relative reliability) of nonlinear methods used to assess human locomotion dynamics. Twenty-four participants of whom twelve were diagnosed with knee osteoarthritis completed 5 min of treadmill walking at self-selected preferred speed on two separate days. Lower limb kinematics were recorded at 100 Hz and hip, knee, and ankle joint angles, three-dimensional (3D) sacrum marker displacement and stride time intervals were extracted for 170 consecutive strides. The largest Lyapunov exponent and correlation dimension were calculated for the joint angle and sacrum displacement data using three different state space reconstruction methods (group average, test-retest average, individual time delay and embedding dimension). Sample entropy and detrended fluctuation analysis (DFA) were applied to the stride time interval time series. Relative reliability was assessed using intraclass correlation coefficients and absolute reliability was determined using measurement error (ME). For both joint angles and sacrum displacement, there was a general pattern that the group average state space reconstruction method provided the highest relative reliability and lowest ME compared to the individual and test-retest average methods. The DFA exhibited good reliability, while the sample entropy showed poor reliability. The results comprise a reference material that can inspire and guide future studies of nonlinear gait dynamics.

Introducing Statistical Persistence Decay: A Quantification of Stride-to-Stride Time Interval Dependency in Human Gait

Stride-to-stride time intervals during human walking are characterised by predictability and statistical persistence quantified by sample entropy (SaEn) and detrended fluctuation analysis (DFA) which indicates a time dependency in the gait pattern. However, neither analyses quantify time dependency in a physical or physiological interpretable time scale. Recently, entropic half-life (ENT½) has been introduced as a measure of the time dependency on an interpretable time scale. A novel measure of time dependency, based on DFA, statistical persistence decay (SPD), was introduced. The present study applied SaEn, DFA, ENT½, and SPD in known theoretical signals (periodic, chaotic, and random) and stride-to-stride time intervals during overground and treadmill walking in healthy subjects. The analyses confirmed known properties of the theoretical signals. There was a significant lower predictability (p = 0.033) and lower statistical persistence (p = 0.012) during treadmill walking compared to overground walking. No significant difference was observed for ENT½ and SPD between walking condition, and they exhibited a low correlation. ENT½ showed that predictability in stride time intervals was halved after 11-14 strides and SPD indicated that the statistical persistency was deteriorated to uncorrelated noise after ~50 strides. This indicated a substantial time memory, where information from previous strides affected the future strides.