Gait-stride-and-frequency-based human intention recognition approach and experimental verification on lower limb exoskeleton

In the research of lower extremity exoskeleton, how to achieve synchronization between human and machine is quite significant. The intention recognition, which can be divided into three categories including EMG-based, EEG-based and biomechanics-based, is one of the effective implementation methods. In this paper, a new biomechanics-based method to realize the intention recognition is proposed. Compared with the mainstream, this method identifies the characteristic value of stride and frequency during walking, which describes human intention mathematically and concretizes the intention of human movement, improving the accuracy of recognition result and streamlining the algorithm. In addition, the impedance model is designed to further correct the recognition error. The main contents of this paper can be roughly summarized as follows. Gait feature event points are detected according to the angular signals of exoskeleton joints and the pressure signals of foot sole during the wearer’s walking process. Then the whole gait cycle is segmented by the identified gait feature event points, which is used to identify the wearer’s gait step and frequency in the gait cycle and output the trajectory transformed from standard gait trajectory by the recognized stride and frequency. Moreover, the interactive force signal collected by the three-dimensional force sensors mounted on the four-legged bar is provided as input to the designed impedance controller to adjust the transformed trajectory again. Also, the final trajectory is input to the Proportion Integral and Differential (PID) controller to realize the motion function of the lower extremity exoskeleton based on the wearer’s intention recognition result. Moreover, a simple hardware platform of lower limb exoskeleton is designed and built for practical experimental verification, which involves three kinds of gait respectively having constant stride, constant frequency and time-varying stride and frequency. The feasibility and reliability of the proposed algorithm can be concluded by analyzing the satisfactory experiment result.