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The exoskeleton robot is a wearable robot that will combine human intelligence with external mechanical energy mechanical power devices, can give extra power or ability to enhance human performance. It is used in the field of military, rehabilitation medical etc as a research hotspot. In order to make lower extremity exoskeleton robot follow human motion, and to lower limb exoskeleton robot real-time control, real-time measurement of human lower limb movement and the pattern recognition of the motion mode are need to be done. According to the lower limb gait analysis, the knee angle measurement points of human lower limb movement perception is selected and the fiber angle sensor is selected to measure the knee angle. Using fractal dimension to characterize the motion characteristics of the lower limbs. The SVM is used for pattern recognition by the value of the fractal feature vectors, then the classification parameters were optimized by the way of network search and cross-validation algorithms. The fiber optic sensing system for lower limb movement can identify the lower limb movement into severe motions: walking, running, climbing the slope, going down the slope, squatting and standing up. The optimization results shows that the best recognition results can reach 95% when nuclear radius is 0.4 and the penalty factor is 45.