Human Body Mixed Motion Pattern Recognition Method Based on MultiSource Feature Parameter Fusion Aiming at the requirement of rapid recognition of the wearerxe2x80x99s gait stage in the process of intelligent hybrid control of an exoskeleton, this paper studies the human body mixed motion pattern recognition technology based on multisource feature parameters. We obtain information on human lower extremity acceleration and plantar analyze the relationship between these parameters and gait cycle studying the motion state recognition method based on feature evaluation and neural network. Based on the actual requirements of exoskeleton per use, 15 common gait patterns were determined. Using this, the studies were carried out on the time domain, frequency domain, and energy feature extraction of multisource lower extremity motion information. The distancebased feature screening method was used to extract the optimal features. Finally, based on the multilayer BP (back propagation) neural network, a nonlinear mapping model between feature quantity and motion state was established. The experimental results showed that the recognition accuracy in single motion mode can reach up to 98.28%, while the recognition accuracy of the two groups of experiments in mixed motion mode was found to be 92.7% and 97.4%, respectively. The feasibility and effectiveness of the model were verified.

Lower Limbs Exoskeleton Control Strategy Based On Optimized Compliance Algorithm Aiming at achieving the compliance control of lower limbs exoskeleton, a compliant control strategy basing on optimized compliance algorithm was proposed. The motion trajectory of human body was collected by using inertial sensors and electromyography sensors, and the information is taken as the reference information to the exoskeleton robot. By introducing muscle activation degree as the feedforward loop to offset the hysteresis phenomenon which is shown in the process of movement, the following movement achieved compliant. The feasibility of this control method is both verified on the simulation software platform and physical prototype. The experimental results show that this control method is effective and feasible in the lower limbs exoskeleton system.