Lower limb sagittal gait kinematics can be predicted based on walking speed, gender, age and BMI

Abstract

Clinical gait analysis attempts to provide, in a pathological context, an objective record that quantifies the magnitude of deviations from normal gait. However, the identification of deviations is highly dependent with the characteristics of the normative database used. In particular, a mismatch between patient characteristics and an asymptomatic population database in terms of walking speed, demographic and anthropometric parameters may lead to misinterpretation during the clinical process. Rather than developing a new normative data repository that may require considerable of resources and time, this study aims to assess a method for predicting lower limb sagittal kinematics using multiple regression models based on walking speed, gender, age and BMI as predictors. With this approach, we were able to predict kinematics with an error within 1 standard deviation of the mean of the original waveforms recorded on fifty-four participants. Furthermore, the proposed approach allowed us to estimate the relative contribution to angular variations of each predictor, independently from the others. It appeared that a mismatch in walking speed, but also age, sex and BMI may lead to errors higher than 5° on lower limb sagittal kinematics and should thus be taken into account before any clinical interpretation.

Influence of spino-pelvic and postural alignment parameters on gait kinematics

“…Moreover, our results showed that increased weight might cause a decreased hip extension in stance (hip flexion: β=0.269, R 2 adjusted = 0.118), along with an attitude of external hip rotation (decreased hip internal rotation in stance: β=-0.232, R 2 adjusted = 0.234), a decreased mobility in the knee (ROM knee flexion/extension: β=-0.360, R 2 adjusted = 0.123), a more external foot progression (mean foot progression in stance: β=-0.410, R 2 adjusted = 0.301) and a longer stance phase (foot off: β=0.273, R 2 adjusted = 0.128). Part of these results are in accordance with recent studies that found that increased Body Mass Index (BMI) was associated with increased hip flexion, that might be due to differences in the location of subjects' center of mass [42,43].…”

Prediction of plausible locomotion using nonlinear kinematic optimization

“…The main contribution of this article is to adapt the method of Nicolas et al (2009): optimizing symmetric and cyclic parametric angular trajectories instead of per-frame inverse kinematics. Contrary to previous works such as (Moissenet et al 2019), we have used a limited set of CP to impose as little knowledge as possible on the angular trajectories to address a wide range of species. In this article, we have minimized the angular momentum, but future works will explore other cost functions, such as minimizing Jerk or energy.…”

“…To simplify the problem, we propose to model angular trajectories as parametric curves based on control points (CP), as suggested in (Nicolas et al 2009;Moissenet et al 2019). As we aim at simulating the walking pattern of various bipedal species, we cannot directly use CP coming from human locomotion.…”

Walking in the Hibbot, an innovative walking aid improves gait characteristics in children with cerebral palsy: a cross-sectional study

“…This might account for a smaller peak vertical ground reaction force. (38) Possibly, higher inertial forces were needed to start walking with the Hibbot because of its additional weight (7 kg) in comparison to the habitual situation (posterior walker or no device) which may partially explain the decreased walking speed.…”