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Biofusion design and parameter optimization for a novel passive assisted knee exoskeleton robot based on eight-bar mechanism

Published online by Cambridge University Press:  09 May 2024

Jun Wei*
Affiliation:
School of Mechanical Engineering, Hebei University of Technology, Tianjin, 300401, China Hebei Key Laboratory of Robot Perception and Human-Machine Integration, Tianjin, 300401, China Intelligent Rehabilitation Device and Detection Technology Engineering Research Center of the Ministry of Education, Tianjin, 300130, China
Shizhao Zhang
Affiliation:
School of Mechanical Engineering, Hebei University of Technology, Tianjin, 300401, China Hebei Key Laboratory of Robot Perception and Human-Machine Integration, Tianjin, 300401, China Intelligent Rehabilitation Device and Detection Technology Engineering Research Center of the Ministry of Education, Tianjin, 300130, China
Jianjun Zhang*
Affiliation:
School of Mechanical Engineering, Hebei University of Technology, Tianjin, 300401, China Hebei Key Laboratory of Robot Perception and Human-Machine Integration, Tianjin, 300401, China Intelligent Rehabilitation Device and Detection Technology Engineering Research Center of the Ministry of Education, Tianjin, 300130, China
*
Corresponding authors: Jun Wei; Email: jun.wei@hebut.edu.cn; Jianjun Zhang; Email: zhjjun@hebut.edu.cn
Corresponding authors: Jun Wei; Email: jun.wei@hebut.edu.cn; Jianjun Zhang; Email: zhjjun@hebut.edu.cn
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Abstract

In an effort to alleviate the issue of knee joint fatigue and injury during lower limb ambulation, a novel passive assisted exoskeleton robot with human–machine interaction is investigated to assist the movement of the human knee joint. The design of the exoskeleton configuration takes into consideration the physiological structure and gait function of the knee joint, ensuring that it satisfies the requirements for motion, force, and gait function of the knee joint. To explore the interaction between the wearer and the exoskeleton, a human–machine kinematic model after wearing exoskeleton is established, which is instrumental in analyzing the integration motion of the wearer and exoskeleton. In addition, the dynamic and static models of the knee joint after wearing the exoskeleton are established, utilizing the Newton–Euler method and force polygon method, respectively, to evaluate the effectiveness of the exoskeleton. Moreover, the size parameters and spring stiffness of the exoskeleton are optimized, using both human body kinematic model and mechanic model. Furthermore, the effectiveness of the exoskeleton in proving assistance is evaluated through human body simulation, using OpenSim. The results indicate that the exoskeleton significantly reduces the knee joint torque by 48.42%.

Information

Type
Research Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press
Figure 0

Figure 1. Knee joint movement and force. (a) Changes of knee joint angle during gait cycle. (b) Changes of knee joint torque during gait cycle. (c) Intra-articular pressure changes of knee joint during gait cycle.

Figure 1

Figure 2. Exoskeleton structure diagram and wearing diagram.

Figure 2

Figure 3. Brief diagram of exoskeleton mechanism.

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Figure 4. Changes of exoskeleton joint stiffness during gait cycle.

Figure 4

Figure 5. Changes of exoskeleton joint stiffness during gait cycle.

Figure 5

Figure 6. Kinematic analysis of mechanism.

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Figure 7. Simplified lower limb model after wearing exoskeleton and single closed chain of human–machine calf space.

Figure 7

Figure 8. Kinematic description of single closed chain in man–machine calf space.

Figure 8

Table I. Exoskeleton size parameters.

Figure 9

Figure 9. Human–machine instantaneous center trajectory.

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Figure 10. Theoretical results and simulation results of sliding degree.

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Figure 11. Rotation degree theoretical results and simulation results.

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Figure 12. The angle of each part during knee flexion.

Figure 13

Figure 13. Auxiliary line in exoskeleton.

Figure 14

Figure 14. Static model of knee joint.

Figure 15

Table II. Exoskeleton size parameters and spring stiffness.

Figure 16

Figure 15. Torque of human knee joint.

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Figure 16. Human–machine interaction force.

Figure 18

Figure 17. Theoretical results and simulation results of joint torque.

Figure 19

Figure 18. Theoretical and simulation results of knee joint internal pressure.

Figure 20

Table III. Constraint conditions of exoskeleton parameters.

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Table IV. The optimized parameters of exoskeleton.

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Figure 19. Comparison of human–machine instantaneous center trajectory.

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Figure 20. Comparison of exoskeleton joint torque and knee joint torque.

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Figure 21. The deviation degree of human–machine binding.

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Figure 22. Rotation angle of human–machine binding.

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Figure 23. Human–machine interaction force at the binding.

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Figure 24. Knee joint torque after assist.

Figure 28

Figure 25. The exoskeleton model imported into ADAMS.

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Figure 26. Comparison of instantaneous center trajectory.

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Figure 27. Comparison of spring elasticity.

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Figure 28. The simulation model is established according to the wearing condition of the exoskeleton.

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Figure 29. Knee joint torque before and after wearing exoskeleton.

Figure 33

Figure 30. Knee joint pressure before and after wearing exoskeleton.

Figure 34

Figure 31. The strength of each muscle. (a) Rectus femoris muscle strength before and after wearing exoskeleton. (b) Lateral femoral muscle strength before and after wearing exoskeleton. (c) Medial femoral muscle strength before and after wearing exoskeleton. (d) Middle femoral muscle strength before and after wearing exoskeleton.