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BACKGROUND: In a patient with severe hemiplegia, the risk of the knee giving way is high during the early stage of gait exercise with an ankle-foot orthosis. However, use of a knee-ankle-foot orthosis has many problems such as large amount of assistance and compensatory motions. To resolve these problems, we have engaged in the development of the Gait Exercise Assist Robot (GEAR). OBJECTIVE: To evaluate the improvement efficiency of walk with GEAR in a stroke patient. METHODS: The subject was a 70-year-old man presented with left thalamus hemorrhage and right hemiplegia. The patient underwent exercise with the GEAR 5 days a week, for 40 minutes per day. We evaluated the Functional Independence Measure score for walk (FIM-walk score) every week. The control group consisted of 15 patients aged 20-75 years with hemiplegia after primary stroke, who had equivalent walking ability with the subject at start. As the primary outcome, we defined improvement efficiency of FIM-walk, which was gain of FIM-walk divided the number of required weeks. RESULTS: Improvement efficiency of FIM-walk of the subject was 1.5, while that of control group was 0.48±3.2 (mean±SD). CONCLUSIONS: GEAR is potentially useful for gait exercise in hemiplegic patients. [ABSTRACT FROM AUTHOR]

Abstract   This paper presents a sensory-motor coordination scheme for a robot hand-arm-head system that provides the robot with the capability to reach an object while pre-shaping the fingers to the required grasp configuration and while predicting the tactile image that will be perceived after grasping. A model for sensory-motor coordination derived from studies in humans inspired the development of this scheme. A peculiar feature of this model is the prediction of the tactile image. The implementation of the proposed scheme is based on a neuro-fuzzy module that, after a learning phase, starting from visual data, calculates the position and orientation of the hand for reaching, selects the best-suited hand configuration, and predicts the tactile feedback. The implementation of the scheme on a humanoid robot allowed experimental validation of its effectiveness in robotics and provided perspectives on applications of sensory predictions in robot motor control. [ABSTRACT FROM AUTHOR]