DESIGN OF BRAIN-CONTROLLED LOWER LIMB EXOSKELETON BASED ON MULTIPLE ENVIRONMENTS

摘要

To improve human ability to adapt to the environment and quality of life, expand its own living range, a brain-controlled lower limb rehabilitation exoskeleton is designed. Firstly, the EEG feature extraction model was established by using the wavelet transform analysis. The wavelet entropy of different frequency band signals and the input signal of the pattern recognition are obtained by using wavelet packet decomposition. Through the EEG signal detection test, the EEG signal recognition accuracy was obtained. Then, the methods of EEG control, pre-programming control, feedback control and neural network control for the exoskeleton system were analysed, and control experiments were carried out. The exoskeleton mathematical model and virtual prototype were established, the rationality of its structural design is verified by the manufacturing of exoskeleton experimental prototype and experimental study. Finally, the trajectory tracking test of the lower limb exoskeleton verified the sensitivity of the exoskeleton movement, the exoskeleton passive control test and the active control test verified the effectiveness of the exoskeleton. Usage under both brain control and pre-programming control demonstrates the exoskeleton fulfill the demanding needs of this application. These results lay the groundwork for further advancement in the brain-controlled exoskeleton.