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EN
The aim of the study was to propose a relatively simple central pattern generator (CPG) model, which can be used to control a lower limb exoskeleton. The mentioned generator and the simulation model of the human gait were developed based on experimental observations of the healthy volunteer's gait recorded using a motion tracking system. In order to reproduce the correct movements of the exoskeleton segments, time series of angles in the joints corresponding to the hip and knee joints were calculated based on tracing the trajectories generated by the CPG and the inverse kinematic relations. The proposed model can be implemented to control the lower limb (extremity) exoskeleton and assist various types of gait abnormality in patients with different motor dysfunction by means of changing the parameters of the control system. The presented experimental data, the developed gait simulation model, and the results of numerical simulations can be treated as guidelines for further improvement of the proposed model and its application in the exoskeleton control system. Although the study is mainly focused on rehabilitation applications, the proposed model is general and can be used also for other purposes such as control of bipedal and multi-legged robots.
EN
Gait recovering after spinal cord injury (SCI) is a regular attempt in neurorehabilitation. For this purpose, various clinical techniques have been proposed until now. However, the feasibility of these techniques has not been theoretically investigated so much. This has been mainly for difficulties of gait modeling in SCI patients. Involving these problems, recently neuromechanical models of gait locomotion have been proposed for examining rehabilitation methods. However, these models were so simple that could not properly express rehabilitation effects. Notably, lesion intensity is a concern that was never attended in prior simulations. Due to this limitation, in this paper a new neuromechanical model is proposed that classifies patients based on intensity of trauma. Explicitly, the complete, severe and non-severe incomplete SCIs are imitated and effects of related clinical rehabi-litations are explored. Remarkably, the model indicates an incredible performance in explaining the rehabilitation effects through presenting the compliant results with clinical information. The suitability of this model is mainly for the applied neuromuscular plan that consists of a combined plan of central pattern generator (CPG) and neural reflexes that controls a double segment limb. The validity of this model is further proved by comparing the kinematic and kinetic results to the experimental data.
EN
Neural networks composed of two or four cells with combined, electrical and inhibitory, synapses and realized for various network topologies were examined. The aim of this study was to determine a set of phases of oscillatory cycle in which different patterns of activity, characteristic for such networks, can be switched under an external stimulus. In particular, we studied susceptibility of switching between in-phase (IP) and anti-phase (AP) patterns (and vice versa). Our results demonstrate that windows of switching between patterns are similar for networks with electrical and mixed synapses and, in general, relatively independent of the network topology. The only effect of the network topology is an increase of the robustness of the AP pattern in networks of ring-like connectivity. The switching window width and thereby the robustness of the transitions between patterns decreases with the increase of the electrical coupling strength.
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