Aiming at the human-computer interaction problem during the movement of the rehabilitation exoskeleton robot, this paper proposes an adaptive human-computer interaction control method based on real-time monitoring of human muscle state. Considering the efficiency of patient health monitoring and rehabilitation training, a new fatigue assessment algorithm was proposed. The method fully combined the human neuromuscular model, and used the relationship between the model parameter changes and the muscle state to achieve the classification of muscle fatigue state on the premise of ensuring the accuracy of the fatigue trend. In order to ensure the safety of human-computer interaction, a variable impedance control algorithm with this algorithm as the supervision link was proposed. On the basis of not adding redundant sensors, the evaluation algorithm was used as the perceptual decision-making link of the control system to monitor the muscle state in real time and carry out the robot control of fault-tolerant mechanism decision-making, so as to achieve the purpose of improving wearing comfort and improving the efficiency of rehabilitation training. Experiments show that the proposed human-computer interaction control method is effective and universal, and has broad application prospects.
本文提出了一种基于人体肌肉状态实时监测的自适应人机交互控制方法，用于解决康复外骨骼机器人运动过程中的人机交互问题。为了保证患者的健康监控和康复训练效率，提出了一种新的疲劳评估算法，该算法利用人体神经肌骨模型，实现了对肌肉疲劳状态的等级划分。为了保证人机交互的安全性，提出了一种以该算法作为监督环节的变阻抗控制算法。通过实验验证，本文所提出的人机交互控制方法是有效的，具有普遍性，能够改善穿戴舒适度，提高康复训练效率，具有广阔的应用前景。.
Keywords: Electromyography signals; Exoskeleton rehabilitation robot; Fatigue monitoring; Hammerstein model; Impedance control.