Figure 4 - uploaded by Stéphane Armand
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Example of the vertical ground reaction force recorded during the stance phase of the normal gait cycle.
Source publication
Walking is the first way of displacement for human and essential for daily life activities and social participation. The human gait can be analyzed from several points of view and specialties. The aim of this chapter is to describe from a simple manner the normal gait in term of gait cycle, acquisition and development of the gait, joint kinematics,...
Contexts in source publication
Context 1
... the impact force is followed by a loading response. During this short period, the whole foot is in contact with the ground and the vertical GRF increases to attain the first maximum peak force (F1 on Figure 4). After this first peak, the vertical force diminishes corresponding at the mid stance phase (F2 on the Figure 4). ...
Context 2
... this short period, the whole foot is in contact with the ground and the vertical GRF increases to attain the first maximum peak force (F1 on Figure 4). After this first peak, the vertical force diminishes corresponding at the mid stance phase (F2 on the Figure 4). Indeed during this phase, the opposite foot is in the mid swing phase, therefore the whole body weight is supported by the stance limb. ...
Context 3
... the heel lifts away from the ground, the GRF starts increasing once again. This ascending second peak (F3 on the Figure 4) of the GRF corresponds to the second double support. Finally, the GRF pattern starts descending to zero with the pre-swing phase and drops to zero when the foot leaves the ground (Figure 4). ...
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Citations
Template models, such as the Bipedal Spring-Loaded Inverted Pendulum and the Virtual Pivot Point, have been widely used as low-dimensional representations of the complex dynamics in legged locomotion. Despite their ability to qualitatively match human walking characteristics like M-shaped ground reaction force (GRF) profiles, they often exhibit discrepancies when compared to experimental data, notably in overestimating vertical center of mass (CoM) displacement and underestimating gait event timings (touchdown/ liftoff). This paper hypothesizes that the constant leg stiffness of these models explains the majority of these discrepancies. The study systematically investigates the impact of stiffness variations on the fidelity of model fittings to human data, where an optimization framework is employed to identify optimal leg stiffness trajectories. The study also quantifies the effects of stiffness variations on salient characteristics of human walking (GRF profiles and gait event timing). The optimization framework was applied to 24 subjects walking at 40% to 145% preferred walking speed (PWS). The findings reveal that despite only modifying ground forces in one direction, variable leg stiffness models exhibited a >80% reduction in CoM error across both the B-SLIP and VPP models, while also improving prediction of human GRF profiles. However, the accuracy of gait event timing did not consistently show improvement across all conditions. The resulting stiffness profiles mimic walking characteristics of ankle push-off during double support and reduced CoM vaulting during single support.
Predicting an individual's response to an exoskeleton and understanding what data are needed to characterize responses remains challenging. Specifically, we lack a theoretical framework capable of quantifying heterogeneous responses to exoskeleton interventions. We leverage a neural network-based discrepancy modeling framework to quantify complex changes in gait in response to passive ankle exoskeletons in nondisabled adults. Discrepancy modeling aims to resolve dynamical inconsistencies between model predictions and real-world measurements. Neural networks identified models of (i) Nominal gait, (ii) Exoskeleton (Exo) gait, and (iii) the Discrepancy (i.e., response) between them. If an Augmented (Nominal+Discrepancy) model captured exoskeleton responses, its predictions should account for comparable amounts of variance in Exo gait data as the Exo model. Discrepancy modeling successfully quantified individuals' exoskeleton responses without requiring knowledge about physiological structure or motor control: a model of Nominal gait augmented with a Discrepancy model of response accounted for significantly more variance in Exo gait (median R2 for kinematics (0.928-0.963) and electromyography (0.665-0.788), (p<0.042)) than the Nominal model (median R2 for kinematics (0.863-0.939) and electromyography (0.516-0.664)). However, additional measurement modalities and/or improved resolution are needed to characterize Exo gait, as the discrepancy may not comprehensively capture response due to unexplained variance in Exo gait (median R2 for kinematics (0.954-0.977) and electromyography (0.724-0.815)). These techniques can be used to accelerate the discovery of individual-specific mechanisms driving exoskeleton responses, thus enabling personalized rehabilitation.
The continuous advances in sensing and telecommunications fields have boosted the development of new technologies towards the improvement of healthcare systems. This drive of knowledge is required to address the rise of life expectancy of an ageing population with increased associated physical impairments, in order to ease the burden on already stressed healthcare systems. Towards such objective, this paper explores the use of a wearable optical fiber based solution for the ankle plantar-dorsi-flexion monitoring, to be used in the evaluation of the progress of physical rehabilitation therapies. The proposed device is a non-invasive, small size and easy to use solution, based on a cost-effective in-line Fabry-Perot interferometer, complemented with new dynamic interrogation techniques that allow the angular monitoring of the ankle-shank joint during gait (walking). The designed and produced wearable solution was calibrated and tested in a laboratory environment, with promising results that prove the accuracy of the wearable device, as it falls within the expected pattern of an ankle plantar-dorsi-flexion movement during gait. The developed system can be used for rehabilitation therapies monitoring, to be integrated in exoskeletons or applied for athletes’ performance analysis and optimization, during injury recovery.
Gait detection is crucial especially in active prosthetic leg control mechanism. Vision system, floor sensors, and wearable sensors are the popular methods proposed to collect data for gait detection. However, in active prosthetic leg control, a tool that is practical in its implementation and is able to provide rich gait information is important for effective manipulation of the prosthetic leg. This paper aims to ascertain the feasibility of the piezoelectric-based in-socket sensory system that is hypothesized to be practical in implementation and provide sufficient information as a wearable gait detection tool for transfemoral prosthetic users. Fifteen sensors were instrumented to the anterior and posterior internal wall of a quadrilateral socket. One transfemoral amputee subject donned the instrumented socket and performed two walking routines; single stride and continuous walking. The sensors’ responses from both routines were analyzed with respect to the gait phases. The results suggested that the sensors output signal corresponds to the force components behavior of the stump while performing gait. All sensors were seen active during the first double support period (DS1). The anterior sensors were prominent during the initial swing (Sw), while posterior sensors were active during terminal Sw. These findings correspond with the muscle activity during the respective phases. Besides, the sensors also show significant pattern during single support and the second double support (DS2) phase. Thus, it can be deduced that the proposed sensory system is feasible to be used as a gait phase identification tool.
Recent studies predict that by 2060, people aged 65 or more will account to one third of the European population. These statistics raise questions regarding the sustainability of the society, so technological solutions have been emerging to prolong the active age of European citizens. One of the main impairments for elders to have an active life is an increasing difficulty in performing a natural gait. Some exoskeletons were identified with elder gait assistance as one of several features. However, to cover other features, these exoskeletons are generally large and bulky. Wearing a very visible device may cause an unwanted awkwardness. For this reason, the authors are developing an active exoskeleton whose sole purpose is to assist the gait of an elderly person. The proposed system is based on a low-profile design, allowing a smaller frame that permits the device to be worn beneath loose clothing, making it more desirable to wear in public by reducing social awkwardness. The framework for designing the mechanical support for the exoskeleton is presented. Three-dimensional human models were imported into Solidworks, developing the components assembled around the human models and performing finite element analysis simulations to test the system with subject of different weights. The design can adapt to several body shapes using variable distances between components. The exoskeleton frame supports 7 degrees of freedom for each lower limb.
