BACKGROUND: Recently studies showed that robot-assisted therapy can improve recovery of upper-limb in subacute and chronic stroke patients, but the studies on robot-assisted therapy in acute stroke patients are few.
OBJECTIVE: To study the effects of robot-assisted therapy on upper-limb in acute stroke patients.
METHODS: A total of 30 acute stroke patients were divided into two groups according to the wish. The patients in conventional therapy group received a conventional rehabilitative program including usual facilitation techniques, neuromuscular electrical stimulation, acupuncture therapy and so on. The patients in robot-assisted therapy group received robot-assisted therapy on the basis of conventional rehabilitative program. This kind of robot consists of adaptive upper-limb weight support, intelligence feedback and three-dimension training systems. A single or multiple joint training can be carried out in the virtual reality environment.
RESULTS AND CONCLUSION: After treatment Fugl-Meyer Score of the upper extremity assessment (FMA) and the functional independence measure (FIM) were better than the scores before treatment both in the two groups significantly. At 3 weeks after treatment, there was no statistical difference in the FMA Scores in the two groups (P=0.075), but at 3 months the patients in robot-assisted therapy group gained better scores than conventional therapy group significantly (P < 0.01). The differences were not significant in the FIM Scores between the two groups both at 3 weeks or 3 months after treatment (P > 0.05). The changes of scores both on FMA and FIM compared with before treatment in robot-assisted therapy group were better than conventional therapy group statistically (P < 0.05). It could be concluded that robot-assisted therapy gained better motor function of upper limb in acute stroke patients on the basis of conventional therapy. Robot-assisted therapy also could change much more motor function and activities of daily living. (далее…)

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Wearable robots have defined a new horizon for elderly and disabled people, to regain control of their limbs, as well as for healthy people, to increase their abilities of hard missions execution. The present paper deals with the control of a lower limb orthosis applied at the knee joint level for rehabilitation purposes. A bounded control torque is developed in order to guarantee the asymptotic stability of the knee orthosis. The control law respects the physical constraints of the system. Moreover, it is robust with respect to external disturbances. The effectiveness of the control torque is tested in real-time using the EICOSI orthosis of the LISSI Lab.

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This document provides a review of the techniques and therapies used in gait rehabilitation after stroke. It also examines the po-ssible benefits of including assistive robotic devices and brain-computer interfaces in this field, according to a top-down appro-ach, in which rehabilitation is driven by neural plasticity. The methods reviewed comprise classical gait rehabilitation techniques (neurophysiological and motor learning approaches), functional electrical stimulation (FES), robotic devices, and brain-computer interfaces (BCI). From the analysis of these approaches, we can draw the following conclusions. Regarding classical rehabilitation techniques, there is insufficient evidence to state that a particular approach is more effective in promoting gait recovery than other. Combination of different rehabilitation strategies seems to be more effective than over-ground gait training alone. Robotic devices need further research to show their suitability for walking training and their effects on over-ground gait. The use of FES combined with different walking retraining strategies has shown to result in improvements in hemiplegic gait. Reports on non-inva-sive BCIs for stroke recovery are limited to the rehabilitation of upper limbs; however, some works suggest that there might be a common mechanism which influences upper and lower limb recovery simultaneously, independently of the limb chosen for the rehabi-litation therapy. Functional near infrared spectroscopy (fNIRS) enables researchers to detect signals from specific regions of the cortex during performance of motor activities for the development of future BCIs. Future research would make possible to analyze the impact of rehabilitation on brain plasticity, in order to adapt treatment resources to meet the needs of each patient and to optimize the recovery process.

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Robot-assisted upper limb rehabilitation training was proposed instead of the traditional rehabilitation training in this paper. The basic principle of motor function recovery is the medical theoretical basis of robot-assisted rehabilitation training, and contains two aspects, one is that the central nervous system has a high degree of plasticity after the brain injury, and the other is that motor function recovery can be achieved through motor relearning programme. Based on the analysis of the human upper limb, the design of the upper limb rehabilitation robot with an exoskeleton structure and three degrees of freedom (DOFs) that resembles the human upper limb was completed. According to the medical theory, robot-in-charge and patient-in-charge training models were developed for exercise therapy.

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We investigated small-scale hydraulic power system using a system level analysis, where small-scale refers to systems generating 10 to 100 Watts output power, to determine whether the high power density advantage of hydraulic power system holds at small sizes. Hydraulic system power density was analyzed with simple mathematical models and compared to an equivalent hypothetical electromecha-nical system constructed from high-end off-the-shelf components. Calculation results revealed that high operating pressures are needed for smallscale hydraulic power systems to be lighter than the equivalent electromechanical system.

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