The effect of including a mobile arch, toe joint, and joint coupling on predictive neuromuscular simulations of human walking.

Predictive neuromuscular simulations are a powerful tool for studying the biomechanics of human walking, and deriving design criteria for technical devices like prostheses or biorobots. Good agreement between simulation and human data is essential for transferability to the real world. The human foot is often modeled with a single rigid element, but knowledge of how the foot model affects gait prediction is limited. Standardized procedures for selecting appropriate foot models are lacking. We performed 2D predictive neuromuscular simulations with six different foot models of increasing complexity to answer two questions: What is the effect of a mobile arch, a toe joint, and the coupling of toe and arch motion through the plantar fascia on gait prediction? and How much of the foot's anatomy do we need to model to predict sagittal plane walking kinematics and kinetics in good agreement with human data? We found that the foot model had a significant impact on ankle kinematics during terminal stance, push-off, and toe and arch kinematics. When focusing only on hip and knee kinematics, rigid foot models are sufficient. We hope our findings will help guide the community in modeling the human foot according to specific research goals and improve neuromuscular simulation accuracy.

Foot function enabled by human walking dynamics.

Bipedal walking, the habitual gait for man, is rather unique in nature and poses particular challenges for balance and propulsion. The characteristic double-humped ground reaction force profile has been widely observed but not put into functional context. We propose a mathematical model that captures the dynamics of the human foot in walking including the characteristic motion of the center of pressure. Using this model, we analyze the functional interplay of all essential biomechanical contributors to foot dynamics in walking. Our results demonstrate the intricate interplay of a self-stabilizing mechanism which allows extending a leg's stance phase while simultaneously powering rapid swing by condensing the essentials of foot dynamics into a reductionist, biomechanical model. A theory is presented which identifies the foot to be the key functional element and which explains the global dynamics of human walking. The provided insights will impact gait therapy and rehabilitation, the development of assistive devices, such as leg prostheses and exoskeletons, and provide guidelines for the design and control of versatile humanoid robots.

Ground reaction forces intersect above the center of mass in single support, but not in double support of human walking.

There are various simplifying models that describe balance strategies of human walking. In one model it is assumed that ground reaction forces are directed to a point (virtual pivot point) above the center of mass during the whole stride. This was observed in several experimental investigations, but only for the single support phase. It has not yet been concretely considered whether humans use the same stabilization strategy during the double support phase. For analyzing this, nine volunteers walked at self-selected speed while kinetic and kinematic data were measured. We found that in contrast to the single support phase, where the virtual pivot point was significantly above the center of mass, in the double support phase of human walking the ground reaction forces point around the center of mass with a small spread (R2=92.5%). The different heights of the virtual pivot point in the different support phases could be caused by the vertical movement of the center of mass, which has a lower amplitude in the double support phase. This is also reflected in the ground reaction forces, whereby the ratio of the horizontal and vertical ground reaction forces can explain the height of the virtual pivot point. In the double support phase the ratio is shifted in favor of the horizontal component compared to the single support phase, because of a shorter contact time and a delayed braking impulse. Thus, the whole body seems to rotate around the center of mass, which presumably minimizes required energy.

Don't break a leg: running birds from quail to ostrich prioritise leg safety and economy on uneven terrain.

Cursorial ground birds are paragons of bipedal running that span a 500-fold mass range from quail to ostrich. Here we investigate the task-level control priorities of cursorial birds by analysing how they negotiate single-step obstacles that create a conflict between body stability (attenuating deviations in body motion) and consistent leg force-length dynamics (for economy and leg safety). We also test the hypothesis that control priorities shift between body stability and leg safety with increasing body size, reflecting use of active control to overcome size-related challenges. Weight-support demands lead to a shift towards straighter legs and stiffer steady gait with increasing body size, but it remains unknown whether non-steady locomotor priorities diverge with size. We found that all measured species used a consistent obstacle negotiation strategy, involving unsteady body dynamics to minimise fluctuations in leg posture and loading across multiple steps, not directly prioritising body stability. Peak leg forces remained remarkably consistent across obstacle terrain, within 0.35 body weights of level running for obstacle heights from 0.1 to 0.5 times leg length. All species used similar stance leg actuation patterns, involving asymmetric force-length trajectories and posture-dependent actuation to add or remove energy depending on landing conditions. We present a simple stance leg model that explains key features of avian bipedal locomotion, and suggests economy as a key priority on both level and uneven terrain. We suggest that running ground birds target the closely coupled priorities of economy and leg safety as the direct imperatives of control, with adequate stability achieved through appropriately tuned intrinsic dynamics.

Impulsive ankle push-off powers leg swing in human walking.

Rapid unloading and a peak in power output of the ankle joint have been widely observed during push-off in human walking. Model-based studies hypothesize that this push-off causes redirection of the body center of mass just before touch-down of the leading leg. Other research suggests that work done by the ankle extensors provides kinetic energy for the initiation of swing. Also, muscle work is suggested to power a catapult-like action in late stance of human walking. However, there is a lack of knowledge about the biomechanical process leading to this widely observed high power output of the ankle extensors. In our study, we use kinematic and dynamic data of human walking collected at speeds between 0.5 and 2.5 m s(-1) for a comprehensive analysis of push-off mechanics. We identify two distinct phases, which divide the push-off: first, starting with positive ankle power output, an alleviation phase, where the trailing leg is alleviated from supporting the body mass, and second, a launching phase, where stored energy in the ankle joint is released. Our results show a release of just a small part of the energy stored in the ankle joint during the alleviation phase. A larger impulse for the trailing leg than for the remaining body is observed during the launching phase. Here, the buckling knee joint inhibits transfer of power from the ankle to the remaining body. It appears that swing initiation profits from an impulsive ankle push-off resulting from a catapult without escapement.

Robots in human biomechanics--a study on ankle push-off in walking.

In biomechanics, explanatory template models are used to identify the basic mechanisms of human locomotion. However, model predictions often lack verification in a realistic environment. We present a method that uses template model mechanics as a blueprint for a bipedal robot and a corresponding computer simulation. The hypotheses derived from template model studies concerning the function of heel-off in walking are analysed and discrepancies between the template model and its real-world anchor are pointed out. Neither extending the ground clearance of the swinging leg nor an impact reduction at touch-down as an effect of heel lifting was supported by the experiments. To confirm the relevance of the experimental findings, a comparison of robot data to human walking data is discussed and we speculate on an alternative explanation of heel-off in human walking, i.e. that the push-off powers the following leg swing.

A model-experiment comparison of system dynamics for human walking and running.

The human musculo-skeletal system comprises high complexity which makes it difficult to identify underlying basic principles of bipedal locomotion. To tackle this challenge, a common approach is to strip away complexity and formulate a reductive model. With utter simplicity a bipedal spring-mass model gives good predictions of the human gait dynamics, however, it has not been fully investigated whether center of mass motion over time of walking and running is comparable between the model and the human body over a wide range of speed. To test the model's ability in this respect, we compare sagittal center of mass trajectories of model and human data for speeds ranging from 0.5 m/s to 4 m/s. For simulations, system parameters and initial conditions are extracted from experimental observations of 28 subjects. The leg parameters stiffness and length are extracted from functional fitting to the subjects' leg force-length curves. With small variations of the touch-down angle of the leg and the vertical position of the center of mass at apex, we find successful spring-mass simulations for moderate walking and medium running speeds. Predictions of the sagittal center of mass trajectories and ground reaction forces are good, but their amplitudes are overestimated, while contact time is underestimated. At faster walking speeds and slower running speeds we do not find successful model locomotion with the extent of allowed parameter variation. We conclude that the existing limitations may be improved by adding complexity to the model.