The will of humans with physical disabilities to move has found realization through the development of powered roboticexoskeleton. In this study, an energy-efficient gait pattern and swing trajectory of the powered robotic exoskeleton was proposed through function distribution analysis and the dynamic-manipulability ellipsoid (DME). To verify its feasibility and the effect of the proposed optimal gait pattern from the point view of the integrated system (human and exoskeleton), simulations were performed in the cases of walking on level ground and stair ascent/descent. Experiments such as on the metabolic cost of the human body with or without the assistance of the exoskeleton were conducted, and the power consumption of the exoskeleton was assessed, with the aim of improving the efficiency of the integrated system.

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Many robotic systems, like surgical robots, robotic hands, and exoskeleton robots, use cable passing through conduits to actuate remote instruments. Cable actuation simplifies the design and allows the actuator to be located at a convenient location, away from the end effector. However, nonlinear frictions between the cable and the conduit account for major losses in tension transmission across the cable, and a model is needed to characterize their effects in order to analyze and compensate for them. Although some models have been proposed in the literature, they are lumped parameter based and restricted to the very special case of a single cable with constant conduit curvature and constant pretension across the cable only. This paper proposes a mathematically rigorous distributed parameter model for cable-conduit actuation with any curvature and initial tension profile across the cable. The model, which is described by a set of partial differential equations in the continuous time-domain, is also discretized for the effective numerical simulation of the cable motion and tension transmission across the cable. Unlike the existing lumped-parameter-based models, the resultant discretized model enables one to accurately simulate the partial-moving/partial-sticking cable motion of the cable-conduit actuation with any curvature and initial tension profile. The model is further extended to cable-conduit actuation in pull-pull configuration using a pair of cables. Various simulations results are presented to reveal the unique phenomena like backlash, cable slacking, interaction between the two cables, and other nonlinear behaviors associated with the cable conduits in pull-pull configuration. These results are verified by experiments using two dc motors coupled with a cable-conduit pair. The experimental setup has been prepared to emulate a typical cable-actuated robotic system. Experimental results are compared with the simulations and various implications are discussed.

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Current manual joysticks have been widely used to con-trol various artificial devices, but they are expensive and composed of mechanically bulky frames. To ad-dress these issues, we developed a myoelectric joystick using surface electromyogram (sEMG) from six mus-cles that make a wrist joint move. Fluid wrist movements were estimated by introducing a non-negative mus-cle synergy matrix and a joint synergy matrix. Only four movements were predefined (wrist extension, wrist flexion, radial deviation, and ulnar deviation) to construct the muscle synergy matrix, but an experimen-tal result showed that a variety of movements (e.g., a combination of wrist extension and ulnar deviation) could be extracted using the joint matrix. This work also could be extended for development of an alterna-tive computer interface and powered wrist prosthesis for individuals with transradial or wrist disarticu-lation level amputation.

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Now more than ever, progresses in information technology applied to rehabilitation robotics give new hopes to people recovering from different kinds of diseases and injuries. Beside the standard application of EMG signals to analyze disabilities or to track progress in rehabilitation, more focus has been put on controlling robot arms and exoskeletons. In recent years, biomechanists have developed very complex neuromusculoskeletal (NM) models of human joints to understand how the nervous system controls muscles and generates movements. Aware of these potentials, we have started a process of simplification to obtain a NM model suitable for the real-time control for a lower extremity exoskeleton. In this paper we present the NM model for the knee previously developed by Lloyd et al. We then investigate the effects of assuming the tendon infinitely stiff and show how this simplification does not affect the capacity of the model to predict muscle force and joint moment. We also assess the decrease in processing time required to calibrate the model and perform runtime estimates of muscles. Finally, we illustrate the implications of our research for the health care economic and social systems.

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Limited research has been done on exoskeletons to enable faster movements of the lower extremities. An exoskeleton’s mechanism can actually hinder agility by adding weight, inertia and friction to the legs; compensating inertia through control is particularly difficult due to instability issues. The added inertia will reduce the natural frequency of the legs, probably leading to lower step frequency during walking. We present a control method that produces an approximate compensation of an exoskeleton’s inertia. The aim is making the natural frequency of the exoskeleton-assisted leg larger than that of the unaided leg. The method uses admittance control to compensate for the weight and friction of the exoskeleton. Inertia compensation is emulated by adding a feedback loop consisting of low-pass filtered acceleration multiplied by a negative gain. This gain simulates negative inertia in the low-frequency range. We tested the controller on a statically supported, single-degree-of-freedom exoskeleton that assists swing movements of the leg. Subjects performed movement sequences, first unassisted and then using the exoskeleton, in the context of a computer-based task resembling a race. With zero inertia compensation, the steady-state frequency of the leg swing was consistently reduced. Adding inertia compensation enabled subjects to recover their normal frequency of swing.

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