Assessing the effects of foot strike patterns and shoe types on the control of leg length and orientation in running.

This research investigates the stabilization of leg length and orientation during the landing phase of running, examining the effects of different footwear and foot strike patterns. Analyzing kinematic data from twenty male long-distance runners, both rearfoot and forefoot strikers, we utilized the Uncontrolled Manifold approach to assess stability. Findings reveal that both leg length and orientation are indeed stabilized during landing, challenging the hypothesis that rearfoot strikers exhibit less variance in deviations than forefoot strikers, and that increased footwear assistance would reduce these deviations. Surprisingly, footwear with a lower minimalist index enhanced post-landing stability, suggesting that cushioning contributes to both force dissipation and leg length stability. The study indicates that both foot strike patterns are capable of effectively reducing task-relevant variance, with no inherent restriction on flexibility for rearfoot strikers. However, there is an indication of potential reliance on footwear for stability. These insights advance our understanding of the biomechanics of running, highlighting the role of footwear in stabilizing leg length and orientation, which has significant implications for running efficiency and injury prevention.

Overground gait adaptability in older adults with type 2 diabetes in response to virtual targets and physical obstacles.

BACKGROUND: To step over an unexpected obstacle, individuals adapt gait; they adjust step length in the anterior-posterior direction prior to the obstacle and minimum toe clearance height in the vertical direction during obstacle avoidance. Inability to adapt gait may lead to falls in older adults with diabetes as the results of the effects of diabetes on the sensory-motor control system. Therefore, this study aimed to investigate gait adaptability in older adults with diabetes. RESEARCH QUESTION: Would diabetes impair gait adaptability and increase sagittal foot adjustment errors? METHODS: Three cohorts of 16 people were recruited: young adults (Group I), healthy older adults (Group II), and older adults with diabetes (Group III). Participants walked in baseline at their comfortable speeds. They then walked and responded to what was presented in gait adaptability tests, which included 40 trials with four random conditions: step shortening, step lengthening, obstacle avoiding, and walking through. Virtual step length targets were 40% of the baseline step length longer or shorter than the mean baseline step length; the actual obstacle was a 5-cm height across the walkway. A Vicon three-dimensional motion capture system and four A.M.T.I force plates were used to quantify spatiotemporal parameters of a gait cycle and sagittal foot adjustment errors (differences between desired and actual responses). Analyses of variance (ANOVA) repeated measured tests were used to investigate group and condition effects on dependent gait parameters at a significance level of 0.05. RESULTS: Statistical analyses of Group I (n = 16), Group II (n = 14) and Group III (n = 13) revealed that gait parameters did not differ between groups in baseline. However, they were significantly different in adaptability tests. Group III significantly increased their stance and double support times in adaptability tests, but these adaptations did not reduce their sagittal foot adjustment errors. They had the greatest step length errors and lowest toe-obstacle clearance, which could cause them to touch the obstacle more. SIGNIFICANCE: The presented gait adaptability tests may serve as entry tests for falls prevention programs.

Effects of diabetes mellitus on step length and minimum toe clearance adaptation.

BACKGROUND: Adaptive gait involves the ability to adjust the leading foot in response to the requirement of dynamic environments during walking. Accurate adjustments of the minimum toe clearance (MTC) height and step length can prevent older people from falling when walking and responding to hazards. Although older people with diabetes fall more frequently than healthy older adults, no previous studies have quantified their adaptive gait abilities. This study aimed to investigate the effects of diabetes mellitus on step length and MTC height adjustments using a non-immersive virtual-reality system. METHODS: Sixteen young adults (26 ± 5 years, 7 females), 16 healthy older adults (68 ± 5 years, 6 females), and 16 older adults with diabetes (70 ± 5 years, 6 females) completed adaptability tests while walking on a treadmill. A computer system visualised a continuous real-time signal of absolute step length and MTC on a monitor. Each person responded to four discrete participant-specific step length and MTC visual targets that were presented on the same signal. Tasks were to match the peaks of interest on each signal to presented targets. Targets were 10% longer or shorter than the mean baseline step length, and 2.5 cm, and 3.5 cm higher than the mean baseline MTC. When a target was displayed, it remained unchanged for 10 consecutive foot displacement adaptation attempts. Then, the target was removed and a new target or the same target was present after 10 consecutive steps and remained for 10 steps. Each target was randomly presented three times (3 × 10). Step length and MTC height adjustments in response to targets were measured and compared among groups. RESULTS: Mean preferred walking speeds were not different among groups significantly when no targets were presented on the monitor in baseline walking. However, when participants walked on a treadmill while attempting to match step lengths or MTC heights to displayed targets on the monitor, the group with diabetes had reduced step length and MTC adjustments compared with other groups significantly. They showed greater errors (differences between their step lengths/MTC heights and presented targets) on the monitor. CONCLUSIONS: This study quantified reduced abilities for older individuals with diabetes to adjust both step length and MTC in response to stimuli compared to healthy older counterparts. Reduced step length and MTC height adjustments can increase falls in at risk populations. The presented virtual-reality system has merits for assessing and training step and MTC adaptation.

Insight into the hierarchical control governing leg stiffness during the stance phase of running.

Leg stiffness plays a key role in the storage and release of elastic energy during stance. However, the extent to which a runner is able to reuse stored energy remains a limiting factor in determining their running effectiveness. In this study, ten habitual rearfoot strikers and ten habitual forefoot strikers were asked to run on a treadmill in three footwear conditions: traditional, neutral, and minimal running shoes. We examined the effect of habitual foot strike pattern and footwear on leg stiffness control within three task-relevant phases of stance (i.e. touch-down, loading, unloading). Control was quantified using stride-to-stride leg stiffness time-series and the coefficient of variability and detrended fluctuation analysis (DFA). The results are interpreted within a theoretical framework that blends dynamic systems theory and optimal feedback control. Results indicate that leg stiffness control is tightly regulated by an active control process during the loading period of stance. In contrast, the touch-down and unloading phases are driven mostly by passive allometric control mechanisms. The effect of footwear on leg stiffness control was inconclusive due to inconsistent trends across three shoe types. However, stiffness control was affected by landing technique. Habitual rearfoot strike runners have reduced DFA values during the touch-down and unloading phases. These sub-phases are associated with an allometric control process and suggests that rearfoot strike runners express a reduction in system complexity for leg stiffness control and hence, a less adaptable system.

Prediction of foot clearance parameters as a precursor to forecasting the risk of tripping and falling.

Tripping and falling is a serious health problem for older citizens due to the high medical costs incurred and the high mortality rates precipitated mostly by hip fractures that do not heal well. Current falls prevention technology encompasses a broad range of interventions; both passive (e.g., safer environments, hip protectors) and active (e.g., sensor-based fall detectors) which attempt to reduce the effects of tripping and falling. However the majority of these interventions minimizes the impact of falls and do not directly reduce the risk of falling. This paper investigates the prediction of gait parameters related to foot-to-ground clearance height during the leg swing phase which have been physically associated with tripping and falling risk in the elderly. The objective is to predict parameters of foot trajectory several walking cycles in advance so that anticipated low foot clearance could be addressed early with more volitional countermeasures, e.g., slowing down or stopping. In this primer study, foot kinematics was recorded with a highly accurate motion capture system for 10 healthy adults (25-32 years) and 11 older adults (65-82 years) with a history of falls who each performed treadmill walking for at least 10 min. Vertical foot displacement during the swing phase has three characteristic inflection points and we used these peak values and their normalized time as the target prediction values. These target variables were paired with features extracted from the corresponding foot acceleration signal (obtained through double differentiation). A generalized regression neural network (GRNN) was used to independently predict the gait variables over a prediction horizon (number of gait cycles ahead) of 1-10 gait cycles. It was found that the GRNN attained 0.32-1.10 cm prediction errors in the peak variables and 2-8% errors in the prediction of normalized peak times, with slightly better accuracies in the healthy group compared to elderly fallers. Prediction accuracy decreased linearly (best fit) at a slow rate with increasing prediction horizon ranging from 0.03 to 0.11 cm per step for peak displacement variables and 0.34 × 10(-3) - 1.81 × 10(-3)% per step for normalized peak time variables. Further time series analysis of the target gait variable revealed high autocorrelations in the faller group indicating the presence of cyclic patterns in elderly walking strategies compared to almost random walking patterns in the healthy group. The results are promising because the technique can be extended to portable sensor-based devices which measure foot accelerations to predict the onset of risky foot clearance, thus leading to a more effective falls prevention technology.

Investigating scale invariant dynamics in minimum toe clearance variability of the young and elderly during treadmill walking.

Current research applying variability measures of gait parameters has demonstrated promise for helping to solve one of the "holy grails" of geriatric research by defining markers that can be used to prospectively identify persons at risk of falling . The minimum toe clearance (MTC) event occurs during the leg swing phase of the gait cycle and is a task highly sensitive to the spatial and balance control properties of the locomotor system. The aim of this study is to build upon the current state of research by investigating the magnitude and dynamic structure from the MTC time series fluctuations due to aging and locomotor disorder. Thirty healthy young (HY), 27 healthy elderly (HE), and 10 falls risk (FR) elderly individuals (who presented a prior history of trip-related falls) participated in treadmill walking for at least 10 min at their preferred speed. Continuous MTC data were collected and the first 512 data points were analyzed. The following variability indices were quantified: 1) MTC mean and standard deviation (SD), 2) PoincarE plot indices of MTC variability (SD1, SD2, SD1/SD2), 3) a wavelet based multiscale exponent beta to describe the dynamic structure of MTC fluctuations, and 4) detrended fluctuation analysis exponent alpha to investigate the presence of long-range correlations in MTC time series data. Results showed that stride-to-stride MTC time series has a nonlinear structure in all three groups when compared against randomly shuffled surrogate MTC data. Test on aging effects showed the MTC central tendency was significantly lower (p < 0.01) and the magnitude of the MTC variability significantly higher (p < 0.01). This trend changed when comparing FR subjects against age-matched HE as both the central tendency (p < 0.01) and magnitude of the variability (p < 0.01) increased significantly in FR. Although the magnitude of MTC variability increased with age, the nonlinear indices represented by alpha, beta, and SD1/SD2 demonstrated that the nonlinear structure of MTC does not change significantly due to aging (p > 0.05). There were, however, significant differences between HY and FR for beta (between scale 1 and 2; p < 0.01) and alpha (p < 0.05). Out of all the variability measures applied, beta(Wv2-4), SD1/SD2, SD2 of critical MTC parameter were found to be potential markers to be able to reliably identify FR from HE subjects. Further research is required to understand the mechanisms underlying the cause of MTC variability.