The spanning set indicates that variability during the stance period of running is affected by footwear

Sensory information the foot receives appears to be related to kinematic variability. Since footwear material densities affect sensory information, footwear may be an important factor that dictates variability. This study hypothesized that modifications in footwear would result in changes in kinematic variability during the running stance period. Subjects ran on a treadmill for three conditions: hard shoe, soft shoe and barefoot. The spanning sets of the mean ensemble curves of the knee and ankle changes for each condition were used to define variability. Variability was significantly larger in the barefoot condition in comparison with the two footwear conditions for both joints. These results suggest that variability can be affected by peripheral sensory information. The spanning set methodology can be utilized to examine changes in variability

An artificial neural network that utilizes hip joint actuations to control bifurcations and chaos in a passive dynamic bipedal walking model

Chaos is a central feature of human locomotion and has been suggested to be a window to the control mechanisms of locomotion. In this investigation, we explored how the principles of chaos can be used to control locomotion with a passive dynamic bipedal walking model that has a chaotic gait pattern. Our control scheme was based on the scientific evidence that slight perturbations to the unstable manifolds of points in a chaotic system will promote the transition to new stable behaviors embedded in the rich chaotic attractor. Here we demonstrate that hip joint actuations during the swing phase can provide such perturbations for the control of bifurcations and chaos in a locomotive pattern. Our simulations indicated that systematic alterations of the hip joint actuations resulted in rapid transitions to any stable locomotive pattern available in the chaotic locomotive attractor. Based on these insights, we further explored the benefits of having a chaotic gait with a biologically inspired artificial neural network (ANN) that employed this chaotic control scheme. Remarkably, the ANN was quite robust and capable of selecting a hip joint actuation that rapidly transitioned the passive dynamic bipedal model to a stable gait embedded in the chaotic attractor. Additionally, the ANN was capable of using hip joint actuations to accommodate unstable environments and to overcome unforeseen perturbations. Our simulations provide insight on the advantage of having a chaotic locomotive system and provide evidence as to how chaos can be used as an advantageous control scheme for the nervous system

Effect of normalization and phase angle calculations on continuous relative phase

The purpose of this investigation was to determine if phase plot normalization and phase angle definitions would have an affect on continuous relative phase calculations. A subject ran on a treadmill while sagittal plane kinematic data were collected with a high­ speed (180Hz) camera. Segmental angular displacements and velocities were used to create phase plots, and examine the coordination between the leg and thigh. Continuous relative phase was calculated with a combination of two different amplitude normalization techniques, and two different phase angle definitions. Differences between the techniques were noted with a root mean square (RMS) calculation. RMS values indicated that there were differences in the configuration of the non-normalized and normalized continuous relative phase curves. Graphically and numerically, it was noted that normalization tended to modify the continuous relative phase curve configuration. Differences in continuous relative phase curves were due to a loss in the aspect ratio of the phase plot during normalization. Normalization tended to neglect the nonlinear forces acting on the system since it did not maintain the aspect ratio of the phase plot. Normalization is not necessary because the arc tangent function accounts for differences in amplitudes between the segments. RMS values indicated that there were profound differences in the continuous relative phase curve when the phase angle was normalized and a phase angle was calculated relative to the right horizontal axi

Original investigation correlated joint fluctuations can influence the selection of steady state gait patterns in the elderly

This investigation utilized a Markov model to investigate the relationship of correlated lower extremity joint fluctuations and the selection of a steady state gait pattern in the young and elderly. Our model simulated the neuromuscular system by predicting the behavior of the joints for the next gait cycle based on the behavior exhibited in the preceding gait cycles. Such dependencies in the joint fluctuations have been noted previously in the literature. We speculated that compared to the young model, the characteristics of the correlated fluctuations in the elderly model would result in the selection of a different steady state gait pattern. The results of our simulation support the notion that correlated fluctuations in the joint kinematics influence the selection of a steady state gait pattern. The steady state gait pattern for the elderly model was dependent the ankle and hip. Conversely, the steady state gait pattern for the young control model was dependent on the behavior of the knee and hip. Based on our model, we suggested that the altered steady state gait patterns observed in the elderly may be due to an altered neuromuscular memory of prior joint behaviors

The aging human neuromuscular system expresses less certainty for selecting joint kinematics during gait

This investigation quantitatively characterized the certainty of the aging neuromuscular system in selecting a joint range of motion during gait based on the statistical concept of entropy. Elderly and young control groups walked on a treadmill at a self-selected pace. Joint angles were calculated for the ankle, knee and hip. We hypothesized that the aging group would exhibit less certainty in selecting a joint range of motion during gait. Our results supported this hypothesis, and indicated that aged individuals demonstrated statistically less certainty for the knee (16.8%) and hip (24.6%). We suggest that neurophysiological changes associated with aging may result in less certainty of the neuromuscular system in selecting a stable gait

An improved surrogate method for detecting the presence of chaos in gait

It has been suggested that the intercycle variability present in the time series of biomechanical gait data is of chaotic nature. However, the proper methodology for the correct determination of whether intercycle fluctuations in the data are deterministic chaos or random noise has not been identified. Our goal was to evaluate the pseudoperiodic surrogation (PPS) [Small et al., 2001. Surrogate test for pseudoperiodic time series data. Physical Review Letters 87(18), 188,101–188,104], and the surrogation algorithms of Theiler et al. [1992. Testing for nonlinearity in time series: the method of surrogate data. Physica D 58(1–4), 77–94] and of Theiler and Rapp [1996. Re-examination of the evidence for low-dimensional, nonlinear structure in the human electroencephalogram. Electroencephalography and Clinical Neurophysiology 98, 213–222], to determine which is the more robust procedure for the verification of the presence of chaos in gait time series. The knee angle kinematic time series from six healthy subjects, generated from a 2-min walk, were processed with both algorithms. The Lyapunov exponent (LyE) and the approximate entropy (ApEn) were calculated from the original data and both surrogates. Paired t-tests that compared the LyE and the ApEn values revealed significant differences between both surrogated time series and the original data, indicating the presence of deterministic chaos in the original data. However, the Theiler algorithm affected the intracycle dynamics of the gait time series by changing their overall shape. This resulted in significantly higher LyE and ApEn values for the Theiler-surrogated data when compared with both the original and the PPS-generated data. Thus, the discovery of significant differences was a false positive because it was not based on differences in the intercycle dynamics but rather on the fact that the time series was of a completely different shape. The PPS algorithm, on the other hand, preserved the intracycle dynamics of the original time series, making it more suitable for the investigation of the intercycle dynamics and the identification of the presence of chaos in the gait time series

Spanning set defines variability in locomotive patterns

The purpose of the investigation was to use the spanning set methodology to quantify variability in locomotive patterns and to compare this method with traditional measures of variability. Subjects ran on a treadmill while sagittal plane kinematic data were collected with a high-speed (180 Hz) camera. Changes in variability were evaluated as the subject ran barefoot and in shoes. Mean ensemble curves for the knee angle during the stance period were created for each condition. From these curves, traditional measures of variability were calculated using the coefficients of variation (CVs), and the mean deviation (MD). Spanning set vectors were defined from the coefficients of polynomials that were fitted to the respective standard deviation curves. The magnitude of the spanning set was determined by calculating the norm of the difference between the two vectors. The normalised difference between the two conditions was 6.6%, 6.9% and 98%, for the MD, CV and spanning sets, respectively. The results indicated that the spanning set was capable of statistically (p\u3c0.05) determining differences in variability between the two conditions. CV and MD measures were unable to detect statistical differences (p\u3e0.05) between the two conditions. The spanning set provides an alternative, and sensitive measure for evaluating differences in variability from the mean ensemble curve

Stepping over obstacles of different heights and varied shoe traction alter the kinetic strategies of the leading limb

This study aims to investigate the effects of shoe traction and obstacle height on friction during walking to better understand the mechanisms required to avoid slippage following obstacle clearance. Ten male subjects walked at a self-selected pace during eight different conditions: four obstacle heights (0%, 10%, 20%, and 40% of limb length) while wearing two different pairs of shoes (low and high traction). Frictional forces were calculated from the ground reaction forces following obstacle clearance, which were sampled with a Kistler platform at 960 Hz. All frictional peaks increased with increases in obstacle height. Low traction shoes yielded smaller peaks than high traction shoes. The transition from braking to propulsion occurred sooner due to altered control strategies with increased obstacle height. Collectively, these results provided insights into kinetic strategies of leading limb when confronted with low traction and high obstacle environments

Lower extremity injury in female basketball players is related to a large difference in peak eversion torque between barefoot and shod conditions

AbstractBackgroundThe majority of injuries reported in female basketball players are ankle sprains and mechanisms leading to injury have been debated. Investigations into muscular imbalances in barefoot versus shod conditions and their relationship with injury severity have not been performed. The purpose of this study was to investigate the effects of wearing athletic shoes on muscular strength and its relationship to lower extremity injuries, specifically female basketball players due to the high incidence of ankle injuries in this population.MethodsDuring pre-season, 11 female collegiate basketball players underwent inversion and eversion muscle strength testing using an isokinetic dynamometer in both a barefoot and shod conditions. The difference between conditions was calculated for inversion and eversion peak torque, time to peak torque as well as eversion-to-inversion peak torque percent strength ratio for both conditions. Lower extremity injuries were documented and ranked in severity. The ranked difference between barefoot and shod conditions for peak torque and time to peak torque as well as percent strength ratio was correlated with injury ranking using a Spearman rho correlation (ρ) with an α level of 0.05.ResultsThe ranked differences in barefoot and shod for peak eversion and inversion torque at 120°/s were correlated with their injury ranking. Ranking of the athletes based on the severity of injuries that were sustained during the season was found to have a strong, positive relationship with the difference in peak eversion torque between barefoot and shod (ρ = 0.78; p = 0.02).ConclusionIt is possible that a large discrepancy between strength in barefoot and shod conditions can predispose an athlete to injury. Narrowing the difference in peak eversion torque between barefoot and shod could decrease propensity to injury. Future work should investigate the effect of restoration of muscular strength during barefoot and shod exercise on injury rates

Motor control of the lower extremity musculature in children with cerebral palsy

The aim of this investigation was to quantify the differences in torque steadiness and variability of the muscular control in children with cerebral palsy (CP) and typically developing (TD) children. Fifteen children with CP (age = 14.2 ± 0.7 years) that had a Gross Motor Function Classification System (GMFCS) score of I-III and 15 age and gender matched TD children (age = 14.1 ± 0.7 years) participated in this investigation. The participants performed submaximal steady-state isometric contractions with the ankle, knee, and hip while surface electromyography (sEMG) was recorded. An isokinetic dynamometer was used to measure the steady-state isometric torques while the participants matched a target torque of 20% of the subject’s maximum voluntary torque value. The coefficient of variation was used to assess the amount of variability in the steady-state torque, while approximate entropy was used to assess the regularity of the steady-state torque over time. Lastly, the distribution of the power spectrum of the respective sEMG was evaluated. The results of this investigation were: 1) children with CP had a greater amount of variability in their torque steadiness at the ankle than TD children, 2) children with CP had a greater amount of variability at the ankle joint than at the knee and hip joint, 3) the children with CP had a more regular steady-state torque pattern than TD children for all the joints, 4) the ankle sEMG of children with CP was composed of higher harmonics than that of the TD children