Vertical Ground Reaction Force Time Research Articles

Assessing spring-mass similarity in elite and recreational runners.

The dynamic complexity and individualization of running biomechanics has challenged the development of objective and comparative gait measures. Here, we present and explore several novel biomechanical metrics for running that are informed by a canonical inter-species gait template-the spring-mass model. The measures assess running mechanics systemically against the template via quantifying characteristics of a runner's kinetics relative to the energy-conserving elastic system-i.e., their "spring-mass similarity". Applying these metrics in a retrospective cohort investigation, we studied the overground kinetics of two heterogenous populations of runners in two footwear conditions: elite and recreational athletes in shod and barefoot conditions. Across all measures and within foot strike types, the elite runners exhibited mechanics that were more similar to those of the ideally elastic spring-mass template. The elite runners had more symmetric bounces, less discrepancy (i.e., greater coordination) between horizontal and vertical kinetic changes, and better fit to a spring-mass vertical ground reaction force time series. Barefoot running elicited greater kinetic coordination in the recreational runners. At a faster speed, the elites further improved their similarity to the template. Overall, the more economical elite group exhibited greater likeness to the linearly elastic, energy-conserving spring-mass system than their recreational counterparts. This study introduces novel biomechanical measures related to performance in distance running. More broadly, it provides new, approachable metrics for systemic quantification of gait biomechanics in runners across all demographics. These metrics may be applied to assess a runner's global biomechanical response to a variety of interventions, including training adaptations, rehabilitation programs, and footwear conditions.

A damped bipedal inverted pendulum for human–structure interaction analysis

The bipedal inverted pendulum with damping has been adopted to simulate human–structure interaction recently. However, the lack of analysis and verification has provided motivation for further investigation. Leg damping and energy compensation strategy are required for the bipedal inverted pendulum to regulate gait patterns on vibrating structures. In this paper, the Hunt–Crossley model is adopted to get zeros contact force at touch down, while energy compensation is achieved by adjusting the stiffness and rest length of the legs. The damped bipedal inverted pendulum can achieve stable periodic gait with a lower energy input and flatter attack angle so that more gaits are available, compared to the template, referred to as spring-load inverted pendulum. The measured and simulated vertical ground reaction force-time histories are in good agreement. In addition, the dynamic load factors are also within a reasonable range. Parametric analysis shows that the damped bipedal inverted pendulum can achieve stable gaits of 1.6 to 2.4 Hz with a reasonable first harmonic dynamic load factor, which covers the normal walking step frequency. The proposed model in this paper can be applied to human–structure interaction analysis.

Running ground reaction forces across footwear conditions are predicted from the motion of two body mass components.

Although running shoes alter foot-ground reaction forces, particularly during impact, how they do so is incompletely understood. Here, we hypothesized that footwear effects on running ground reaction force-time patterns can be accurately predicted from the motion of two components of the body's mass (mb): the contacting lower-limb (m1 = 0.08mb) and the remainder (m2 = 0.92mb). Simultaneous motion and vertical ground reaction force-time data were acquired at 1,000 Hz from eight uninstructed subjects running on a force-instrumented treadmill at 4.0 and 7.0 m/s under four footwear conditions: barefoot, minimal sole, thin sole, and thick sole. Vertical ground reaction force-time patterns were generated from the two-mass model using body mass and footfall-specific measures of contact time, aerial time, and lower-limb impact deceleration. Model force-time patterns generated using the empirical inputs acquired for each footfall matched the measured patterns closely across the four footwear conditions at both protocol speeds (r2 = 0.96 ± 0.004; root mean squared error = 0.17 ± 0.01 body-weight units; n = 275 total footfalls). Foot landing angles (θF) were inversely related to footwear thickness; more positive or plantar-flexed landing angles coincided with longer-impact durations and force-time patterns lacking distinct rising-edge force peaks. Our results support three conclusions: 1) running ground reaction force-time patterns across footwear conditions can be accurately predicted using our two-mass, two-impulse model, 2) impact forces, regardless of foot strike mechanics, can be accurately quantified from lower-limb motion and a fixed anatomical mass (0.08mb), and 3) runners maintain similar loading rates (ΔFvertical/Δtime) across footwear conditions by altering foot strike angle to regulate the duration of impact. NEW & NOTEWORTHY Here, we validate a two-mass, two-impulse model of running vertical ground reaction forces across four footwear thickness conditions (barefoot, minimal, thin, thick). Our model allows the impact portion of the impulse to be extracted from measured total ground reaction force-time patterns using motion data from the ankle. The gait adjustments observed across footwear conditions revealed that runners maintained similar loading rates across footwear conditions by altering foot strike angles to regulate the duration of impact.

Running impact forces: from half a leg to holistic understanding – comment on Nigg et al.

Running impact forces have immediate relevance for the muscle tuning paradigm proposed here and broader relevance for overuse injuries, shoe design and running performance. Here, we consider their mechanical basis. Several studies demonstrate that the vertical ground reaction force-time (vGRFT) impulse, from touchdown to toe-off, corresponds to the instantaneous accelerations of the body’s entire mass (Mb) divided into two or more portions. The simplest, a two-mass partitioning of the body (lower-limb, M1=0.08•Mb; remaining mass, M2=0.92•Mb) can account for the full vGRFT waveform under virtually all constant-speed, level-running conditions. Model validation data indicate that: 1) the non-contacting mass, M2, often accounts for one-third or more of the early “impact” portion of the vGRFT, and 2) extracting a valid impact impulse from measured force waveforms requires only lower-limb motion data and the fixed body mass fraction of 0.08 for M1.

A general relationship links gait mechanics and running ground reaction forces.

The relationship between gait mechanics and running ground reaction forces is widely regarded as complex. This viewpoint has evolved primarily via efforts to explain the rising edge of vertical force-time waveforms observed during slow human running. Existing theoretical models do provide good rising-edge fits, but require more than a dozen input variables to sum the force contributions of four or more vague components of the body's total mass (mb). Here, we hypothesized that the force contributions of two discrete body mass components are sufficient to account for vertical ground reaction force-time waveform patterns in full (stance foot and shank, m1=0.08mb; remaining mass, m2=0.92mb). We tested this hypothesis directly by acquiring simultaneous limb motion and ground reaction force data across a broad range of running speeds (3.0-11.1 m s-1) from 42 subjects who differed in body mass (range: 43-105 kg) and foot-strike mechanics. Predicted waveforms were generated from our two-mass model using body mass and three stride-specific measures: contact time, aerial time and lower limb vertical acceleration during impact. Measured waveforms (N=500) differed in shape and varied by more than twofold in amplitude and duration. Nonetheless, the overall agreement between the 500 measured waveforms and those generated independently by the model approached unity (R2=0.95±0.04, mean±s.d.), with minimal variation across the slow, medium and fast running speeds tested (ΔR2≤0.04), and between rear-foot (R2=0.94±0.04, N=177) versus fore-foot (R2=0.95±0.04, N=323) strike mechanics. We conclude that the motion of two anatomically discrete components of the body's mass is sufficient to explain the vertical ground reaction force-time waveform patterns observed during human running.

Sensors' Ground Reaction Force behavior for both Normal and Parkinson subjects--A qualitative study.

Characterization of normal and abnormal Gait has been a major research field for decades, whether in fall prevention, sports biomechanics or even disease indication. In this paper, we assess time domain statistical properties of the Vertical Ground Reaction Force (VGRF) during moderate-pace walking, aiming eventually to create a reliable mathematical model of VGRF for normal and abnormal cases. For that endeavor, first order statistical analysis was performed upon signal segmentation in order to determine the degree of stationarity and base the model upon it. Furthermore, we performed curve fitting of the VGRF time series between present and past values, which led us to model the waveform with linear regression via Autoregressive Model for both Normal Walking Signals and Parkinson diseased patients' walking signals. However this is done only for one chosen sensor. However, it would be crucial to take the advantage of the array of sensors. Evaluating the cross-covariance between multi-sensor data of a given subject at different time lags capture the most important information. The seasonality in the values give a quite important indications of the behavior of data. The objective behind this analysis is to recommend a preliminary basis to create reliable mathematical model of normal walking signals versus pathological walking signals, that we will emphasize in a complementary work, in the simplest way available and creating fall prevention indicators for old patients.

Neural network-based prediction of missing key features in vertical GRF–time recordings

Ground reaction force (GRF) time recordings are frequently corrupted due to faulty stepping on a force platform during gait, and this results in the loss of valuable data and the need for additional data acquisition. This paper proposes a new approach based on artificial neural networks for the estimation of lost key gait parameters using the available features of an affected GRF–time trace. GRF–time plots were recorded using a force platform during normal walking of 14 young and 13 elderly individuals. Back-propagation neural network models were developed using features extracted from 466 vertical GRF–time characteristics that would be unaffected as inputs, and the likely affected gait features (e.g. stance time (ST), push-off force, (Fmax2) and push-off time (Tmax2)) as output. Performance of the models in predicting ST, Fmax2 and Tmax2 were tested using data from 30 new gait trials. The neural network model predicted the missing STs with 96.5% (±2.6%) accuracy (r > 0.9). Accuracy of the ST prediction deteriorated when push-off force/time data were unavailable for the prediction model. Fmax2 and its time were reconstructed with an accuracy of 95.7% (±2.8%) and 97.6% (±1.7%) respectively. These results suggest that an artificial neural network may be applied to estimate missing ST, Fmax2 or Tmax2 information using features from an affected vertical GRF–time plot, and the method shows good promise for reconstructing gait forces from a corrupted force–time trace.

Compensatory load redistribution of horses with induced weight-bearing forelimb lameness trotting on a treadmill

The study was performed to obtain a detailed insight into the load and time shifting mechanisms of horses with unilateral weight-bearing forelimb lameness. Reversible lameness was induced in 11 clinically sound horses by applying a solar pressure model. Three degrees of lameness (subtle, mild and moderate) were induced and compared with sound control measurements. Vertical ground reaction force-time histories of all four limbs were recorded simultaneously on an instrumented treadmill. Four compensatory mechanisms could be identified that served to reduce structural stress, i.e. peak vertical force on the affected limb: (1) with increasing lameness, horses reduced the total vertical impulse per stride; (2) the diagonal impulse decreased selectively in the lame diagonal; (3) the impulse was shifted within the lame diagonal to the hindlimb and in the sound diagonal to the forelimb; (4) the rate of loading and the peak forces were reduced by prolonging the stance duration. Except in the diagonal hindlimb, where peak vertical forces increased slightly in the moderate lameness condition, no equivalent compensatory overload situation was observed in the other limbs. Specific force and time information of all four limbs allow the unequivocal identification of the affected limb.