Force-feedback during human walking

Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model

Objective.Studying the neural components regulating movement in human locomotion is obstructed by the inability to perform invasive experimental recording in the human neural circuits. Neuromechanical simulations can provide insights by modeling the locomotor circuits. Past neuromechanical models proposed control of locomotion either driven by central pattern generators (CPGs) with simple sensory commands or by a purely reflex-based network regulated by state-machine mechanisms, which activate and deactivate reflexes depending on the detected gait cycle phases. However, the physiological interpretation of these state machines remains unclear. Here, we present a physiologically plausible model to investigate spinal control and modulation of human locomotion.Approach.We propose a bio-inspired controller composed of two coupled CPGs that produce the rhythm and pattern, and a reflex-based network simulating low-level reflex pathways and Renshaw cells. This reflex network is based on leaky-integration neurons, and the whole system does not rely on changing reflex gains according to the gait cycle state. The musculoskeletal model is composed of a skeletal structure and nine muscles per leg generating movement in sagittal plane.Main results.Optimizing the open parameters for effort minimization and stability, human kinematics and muscle activation naturally emerged. Furthermore, when CPGs were not activated, periodic motion could not be achieved through optimization, suggesting the necessity of this component to generate rhythmic behavior without a state machine mechanism regulating reflex activation. The controller could reproduce ranges of speeds from 0.3 to 1.9 m s-1. The results showed that the net influence of feedback on motoneurons (MNs) during perturbed locomotion is predominantly inhibitory and that the CPGs provide the timing of MNs' activation by exciting or inhibiting muscles in specific gait phases.Significance.The proposed bio-inspired controller could contribute to our understanding of locomotor circuits of the intact spinal cord and could be used to study neuromotor disorders.

Interventions to Improve Walking in Older Adults

Interventions to improve walking in older adults have historically been multifactorial (i.e. strengthening, endurance and flexibility programs) focusing on improving the underlying impairments. These impairment-based programs have resulted in only modest improvements in walking. In older adults, walking is slow, less stable, inefficient, and the timing and coordination of stepping with postures and phases of gait is poor. We argue the timing and coordination problems are evidence of the loss of motor skill in walking. Taking a lesson from the sports world and from neurorehabilitation, task-oriented motor learning exercise is an essential component of training to improve motor skill and may be a beneficial approach to improving walking in older adults. In this article we: 1) briefly review the current literature regarding impairment-based interventions for improving mobility, 2) discuss why the results have been only modest, and 3) suggest an alternative approach to intervention (i.e. task oriented motor learning).

Review of models for the generation of multi-joint movements in 3-D

Most studies in motor control have focused on movements in two dimensions and only very few studies have systematically investigated movements in three dimensions. As a consequence, the large majority of modeling studies for motor control have tested the predictions of these models using movement data in 2D. As we will explain, movements in 3D cannot be understood from movements in 2D by adding just another dimension. The third dimension adds new and unexpected complexities. In this chapter we will explore the frames of reference, which are used in mapping sensory information about movement targets into motor commands and muscle activation patterns. Moreover, we will make a quantitative comparison between the predictions of various models in the literature with the outcome of 3D movement experiments. Quite surprisingly, none of the existing models is able to explain the data in different movement paradigms.

Bifurcation and stability analysis in musculoskeletal systems: a study in human stance

Reflexes are important in the control of such daily activities as standing and walking. The goal of this study is to establish how reflexive feedback of muscle length, velocity, and force can lead to stable equilibria (i.e., posture) and limit cycles (e.g., ankle clonus and gait). The influence of stretch reflexes on the behavior and stability of musculoskeletal systems was examined using a model of human stance. We computed branches of fold and Hopf bifurcations by numerical bifurcation analysis of the model. These fold and Hopf branches divide the parameter space, constructed by the reflexive feedback gains, into regions of different behavior: unstable posture, stable posture, and stable limit cycles. These limit cycles correspond to a neural deficiency, termed ankle clonus. We also linked bifurcation analysis to known biomechanical concepts by linearizing the model: the fold branch corresponds to zero ankle stiffness and defines the minimal muscle length feedback necessary for stable posture; the Hopf branch is related to unstable reflex loops. Crossing the Hopf branch can lead to the above-mentioned stable limit cycles. The Hopf branch reduces with increasing time delays, making the subject's posture more susceptible to unstable reflex loops. This might be one of the reasons why elderly people, or those with injuries to the central nervous system, often have trouble with standing and other posture tasks. The influence of cocontraction and force feedback on the behavior of the posture model was also investigated. An increase in cocontraction leads to an increase in ankle stiffness (i.e., intrinsic muscle stiffness) and a decrease in the effective reflex loop gain. On the one hand, positive force feedback increases the ankle stiffness (i.e., intrinsic and reflexive muscle stiffness); on the other hand it makes the posture more susceptible to unstable reflex loops. For negative force feedback, the opposite is true. Finally, we calculated areas of reflex gains for perturbed stance and quiet stance in healthy subjects by fitting the model to data from the literature. The overlap of these areas of reflex gains could indicate that stretch reflexes are the major control mechanisms in both quiet and perturbed stance. In conclusion, this study has successfully combined bifurcation analysis with the more common biomechanical concepts and tools to determine the influence of reflexes on the stability and quality of stance. In the future, we will develop this line of research to look at rhythmic tasks, such as walking.

The special nature of human walking and its neural control

Walking the way we do is inherently unstable. Sophisticated neurological control systems are required to ensure that we progress and maintain our balance at the same time. Most of what is known about the functional organization of these neurological control systems is inferred from studies on animals. Here, I compare selected studies on the neural control of human walking with similar studies in reduced animal preparations. The simple monosynaptic reflex appears to be controlled by comparable mechanisms in walking cats and humans. However, peripheral feedback mechanisms suggested to contribute to the switch from stance to swing on the basis of experiments in reduced cat preparations have little influence during human walking. A cat whose spinal cord has been completely transected can be made to walk on a treadmill by drug injections, but such an immediate effect of pharmacological intervention is not seen in humans. However, there have been reports that pharmacological intervention can improve the walking of patients with incomplete spinal cord injury, especially when pharmacological treatment is combined with training.