[Efficiency and control performance of man in followins stochastic signals].
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The gait of current two-legged walking machines differs from that of humans, although the kinematic structures of these machines' legs frequently imitate human limbs. This paper presents a method of generating the trajectories of hip and knee joint angles resulting in a gait pattern similar to that of a human. For this purpose the solutions of coupled van der Pol oscillator equations are utilised. There is much evidence that these equations can be treated as a good model of the central pattern generator generating functional (also locomotional) rhythms in living creatures. The oscillator equations are solved by numerical integration. The method of changing the type of gait by changing appropriate parameter values in the oscillator equations is presented (change of velocity and trajectory of leg-ends). The results obtained enable enhanced control of two-legged walking systems by including gait pattern generators which will assume a similar role to that of biological generators.
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In biological systems, the task of computing a gait trajectory is shared between the biomechanical and nervous systems. We take the perspective that both of these seemingly different computations are examples of physical computation. Here we describe the progress that has been made toward building a minimal biped system that illustrates this idea. We embed a significant portion of the computation in physical devices, such as capacitors and transistors, to underline the potential power of emphasizing the understanding of physical computation. We describe results in the exploitation of physical computation by (1) using a passive knee to assist in dynamics computation, (2) using an oscillator to drive a monoped mechanism based on the passive knee, (3) using sensory entrainment to coordinate the mechanics with the neural oscillator, (4) coupling two such systems together mechanically at the hip and computationally via the resulting two oscillators to create a biped mechanism, and (5) demonstrating the resulting gait generation in the biped mechanism.
In this paper the author presents a mathematical model of a device that can be seen as a segment of an artificial worm (following the paradigm "earthworm") and as an artificial muscle as well. Confining considerations to statics, the model shows up as an ordinary parameter-dependent boundary value problem. It is tackled numerically in various particular forms by means of Maple and thus gives a good view of the segment's behavior during inflation and under longitudinal load. Segments of maximal volume present a useful preliminary stage of the investigations.
Stroke is the leading cause of permanent disability despite continued advances in prevention and novel interventional treatments. Post-stroke neuro-rehabilitation programs teach compensatory strategies that alter the degree of permanent disability. Robotic devices are new tools for therapists to deliver enhanced sensorimotor training and concentrate on impairment reduction. Results from several groups have registered success in reducing impairment and increasing motor power with task-specific exercise delivered by the robotic devices. Enhancing the rehabilitation experience with task-specific repetitive exercise marks a different approach to the patient with stroke. The clinical challenge will be to streamline, adapt, and expand the robot protocols to accommodate healthcare economies, to determine which patients sustain the greatest benefit, and to explore the relationship between impairment reduction and disability level. With these new tools, therapists will measure aspects of outcome objectively and contribute to the emerging scientific basis of neuro-rehabilitation.
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