NIU Huiqi 1,2,3 , ZHANG Bi 1,2 , LIU Ligang 1,2,4 , ZHAO Yiwen 1,2 , ZHAO Xingang 1,2
  • 1. State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, P. R. China;
  • 2. Institutes of Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, P. R. China;
  • 3. College of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang 110159, P. R. China;
  • 4. College of Information Science and Engineering, Northeastern University, Shenyang 110819, P. R. China;
ZHAO Xingang, Email: zhaoxingang@sia.cn
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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.

Citation: NIU Huiqi, ZHANG Bi, LIU Ligang, ZHAO Yiwen, ZHAO Xingang. Human muscle fatigue monitoring method and its application for exoskeleton interactive control. Journal of Biomedical Engineering, 2023, 40(4): 654-662. doi: 10.7507/1001-5515.202211020 Copy

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