The current research status and the problems had been summarized about the exoskeleton intelligence systems in worldwide. Human lower limbs movement data had been collected by using the VICON 460 infrared motion capture system, NOVEL pedar insole plantar pressure measure system and CASIO high speed camera. After the data had been researched, the key characteristics parameters were obtained for the human motion recognition. The results indicated that the optimal knee joint ankle was at 157°, as the assisted power was added. Foot arch GHI peak force was at 80N when hopping upward occurred, but foot arch GHI peak force was less when hopping forward occurred. The Lower Limb Exoskeleton Intelligence System model(LLEIS) had been accomplished under UG NX6.0 and exported into ADAMS R3 for the kinematics and dynamics simulation. The agreement of the final computation results with the experimental data indicates this system could be used to assist human hopping intelligently and enhance the effect of the hopping in the field of the human performance augmentation.

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