Abstract
Rehabilitation robot is promising to be an effective therapy tool for post stroke patients, while the optimal robotic therapy paradigm is still unknown, which is partly because there is no standard method for performing clinical validation study of the rehabilitation robot. On the other hand, rehabilitation robots are normally equipped with several kinds of sensors, but there are few researches on analysing and fusing of the training information recorded by the robot. In this study, we introduce a novel upper limb rehabilitation robot with the force feedback ability and virtual reality training function, and a clinical trial is conducted by comparing the conventional therapy and robotic therapy. During the training, the robot records kinematic, kinetic and sEMG (surface electromyography) signals, and by analysing and fusing these data the recovery process are exploited from both short and long terms, small muscle activities and large limb movements.
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