下肢康复机器人的自适应人机交互控制策略

针对康复机器人运动过程中的人机交互性问题，提出一种下肢康复机器人自适应人机交互控制策略.提取伸屈运动中下肢表面肌电信号（Surface electromyography，sEMG）和足底压力特征，分别用于表征下肢运动意图和人机交互力（Interaction force，IF）信息，建立基于sEMG-IF的人机交互信息融合模型，实现下肢康复机器人运动轨迹的在线规划；考虑主动康复运动过程中的人机交互作用，建立具有时变动态特性的人机系统动力学模型，设计间接模糊自适应控制器对期望轨迹进行跟踪控制，实现下肢康复机器人自适应人机交互控制.通过对5名被试者进行下肢康复机器人运动控制实验研究，验证所提方法的可行性和有效性.

Adaptive Interaction Control for Lower Limb Rehabilitation Robots

Aiming at the problem of human-machine interaction in rehabilitation robot's movement, we propose an adaptive control strategy for lower limb rehabilitation robots. During flexion and extension, the surface electromyography (sEMG) of lower limbs and plantar pressure features are extracted respectively to represent lower limbs' motion intention and interaction force (IF). An sEMG-IF based human-machine interaction and information fusion model is established to program the motion trails of the rehabilitation robot online. Considering the human-machine interaction in active rehabilitation, a man-machine system dynamic model with time-varying dynamic characteristics is established. An indirect fuzzy adaptive controller is designed to trace and control the desired trajectory, and achieve adaptive interactive control of the lower limb rehabilitation robot. Validity and feasibility of the proposed strategy are verified by analysis of the data from 5 subjects under limb movement with the rehabilitation robot.