This work introduces a new driven gait orthosis (DGO) based on the pneumatical exoskeleton leg for locomotor training. This device can drive the lower-limb of a patient in a physiological way on the moving treadmill following the given gait which fits to the individual needs. Therefore, it can help a patient who suffers lower-limbs paralysis to recover his walking ability. Mechanisms were designed based on the optimization from the view of human gait and the Ergonomics. Displacement sensors were mounted to allow a closedloop control consequently to make each limb’s motion as similar as possible to that of the human specimen. Each actuator is controlled by an algorithm, which consists of fuzzy and bang-bang. This solution allowed the existing strong nonlinearities to be easily managed with high response. The satisfying experiments results demonstrated the effect of the hybrid algorithm.

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Robotic-powered exoskeletons and body joint-adapted assistive units are currently under development for the enhancement of human locomotor performance in the military, in industries, and in patients and the elderly with mobility impairments [1]. They free people from much labor and the burdens of many kinds of manual work. For example, when it comes to automation in the industrial field, factory automation has made good progress. Operators (humans) can be included in a conventional manufacturing process with respect to a formal production line and uniform working conditions. Automation outside the production line, however, especially in common manufacturing stages, has several limitations and difficulties in adapting to actual conditions because the industrial field has but a small part in the process due to its operating characteristics. There have been many approaches to the reduction of labor that do not only fully assist but also partly aid workers, such as in the use of extremely heavy payload-oriented construction equipment, which are manipulated by humans. Manual or semi-automatic machine tools are mostly used in contemporary industries.

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The impact of disability on society is great not only on direct treat-ment costs. Invaluable loss of human creative activity and mental wellbeing as well as productivity losses reflect the indirect impact on the disabled individual as well as on society as a whole. Stroke is the leading cause of disability in the industrialised countries. Every year, over 130,000 people in the U.K. suffer strokes, with 13,000 under retirement age. Ischemia or haemorrhage in the brain may be the cause of cerebral vascular accidents which result in strokes (Parker et al., 1986). Fortunately over 65% of patients survive but the majority does have residual disabilities with up to 1/3 having severe disabilities particularly in the upper limb and hand. Hemiplegia, the most common impairment resulting from stroke, leaves the survivor with a stronger unimpaired arm and a weaker impaired one (hemiparesis). Traumatic injuries as well as conditions like muscular dystrophy, arthritis and regional pain syndromes, also add to the major causes of disability and functional dependence. Deficits in motor control and coordination synergy patterns, spasticity and pain are some of the most common symptoms of these condi-tions (Parker et al., 1986).

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This thesis addresses two main issues of devices that assist human movements: One is stability of the coupled human-robot system, the other is how to make the human the master of the device. Firstly, passive control of exoskeletons with Series Elastic Actuators (SEAs) is investigated. SEAs decouple motor inertia from the human by a spring, reducing undesired interac-tion forces as a prerequisite for making the human the master. An important result is that if passivity is desired, the SEA cannot guide the limbs with a higher stiffness than that of the spring. Besides passivity analysis, which does not require a model of the human, also model-based stability analysis of human-robot systems is presented, explicitly addressing nonlinearity, time-variability, input saturation, and uncer-tainty. The example is a Hybrid Neuroprosthesis, which combines an exoskeleton with electrical stimulation of the human muscles. Robustness and performance of different controllers is compared. Conservative over- pproximation enables simple stability analysis of the complex structure, indicating that elastic coupling between human limbs and robot can cause instability. The required model of muscle recruitment dynamics is obtained via identification, using an inverted, anti-causal system description. Finally, a correlation- ased method is proposed to estimate desired motion for impaired or missing human limbs by complementing residual body motion. This way, the assistive device is reduced to a mere tool for the human, who regains control of lost motor functions. All methods are evaluated in simulations and in practical experiments with healthy subjects.

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Despite the exceptional performances we saw during the Beijing Olympics, the average human body is limited in how fast it can run, how high it can leap and how much weight it can carry. However, innovative technologies are emerging in the design of wearable robotic systems, or exoskeletons that might soon stretch those limits. Originally designed for military applications, exoskeleton innovations are slowly blossoming in robotic orthotic devices designed to assist in rehabilitation programs for stroke victims, paraplegics and the mobility disabled. Exoskeletons also have tremendous potential in assisting emergency responders, nursing home and home healthcare workers, as well as farmers and factory workers, by reducing incidences of back strain or injury.

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