Research on exoskeleton gait recognition based on sEMG and foot pressure information introspection

DOI:	10.11809/bqzbgcxb2024.01.037
Keywords:	exoskeleton robot; multimodal information introspection; human robot gait recognition; SVM FCM fusion algorithm
Abstract:	Gait introspection is not accurate enough using a single type of signal so that human robot cooperative walking recognition is carried out under dynamic interaction force excitation. Firstly, multimodal sensors detection platform is designed for sEMG and foot pressure information acquisition. Secondly, the signals are preprocessed by filtering, noise reduction, feature extraction and dimension descending. Thirdly, sEMG signals representing the physiological information of the lower limb are introspected with the foot pressure signals of the motion information, and an exoskeleton gait recognition algorithm is established, which supports multi mode information fusion including vector machine and fuzzy C means (Support Vector Machine Fuzzy C mean algorithm, SVM FCM). Finally, the experiment of human robot cooperation is carried out. The experimental results show that the average recognition rate of human robot gait phase after information fusion reaches 82.49%, which is better than the average recognition rate using a single type of signal. The effectiveness of multimodal information introspection algorithm are verified that human robot cooperation gait can be recognized. The research could be used for motion control of lower limb exoskeleton robot, which is the foundation of human robotcompatible cooperation.
Issue:	Vol. 45 No. 1 (2024)
Published:	2024-01-28
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