Abstract
The structural characteristics of a Body Weight Support System (BWSS) significantly influence the rehabilitation effect and control system of a lower-limb robot. This study considers vibration characteristics to design and optimize a BWSS. First, the design principles of the BWSS are formulated, and the force of the system during the rehabilitation training process is analyzed. Second, the BWSS optimization model is established by considering the vibration characteristics, including the design object, selected materials, design variables, optimization objective functions and constraints in static and dynamic analyses. Third, a hybrid multi-objective optimization method combining the finite element method, Kriging metamodel and Multi-Objective Genetic Algorithm (MOGA) is proposed. After performing optimization, the Kriging metamodel is discussed, and the final design parameters of a single-arm support structure are obtained by the MOGA. Finally, different MOGA parameters and the screening algorithm are compared and analyzed. Simultaneously, the experimental vibration acceleration data and the shock data of the actual original rehabilitation robot are compared with the numerical results of the optimized design. The numerical results indicate that the proposed hybrid multi-objective optimization method is reliable in terms of designing the BWSS, and the vibration characteristics of the designed BWSS are improved over those of the actual original BWSS.
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Acknowledgements
The authors would like to thank Professor Jun Ni, Professor Emeritus of Mechanical Engineering, and Dr. Joseph Cohen, a current postdoctoral research fellow, both at the University of Michigan, for their thorough review and recommendations on the paper.
Funding
This work was supported in part by the National Natural Science Foundation of China (Grant No. 52075177), the National Key Research and Development Program of China (Grant No. 2021YFB3301400), Research Foundation of Guangdong Province (Grant No. 2019A050505001).
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The results given in this paper are based on the flow chart presented in Fig. 9. The relevant algorithmic settings are shown in Sect. 4, and the calculation results are shown in Table 5. To replicate the results, the original calculation document is provided as supplementary material.
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Appendices
Appendix 1: wearing steps of the rehabilitation robot
The wearing steps are shown in Fig. 20 and are described as follows:
Step 1 Place a slope behind the rehabilitation treadmill and then rotate the support arm to make room for the patient and wheelchair to drive up the slope.
Step 2 The medical staff pushes the patient onto the rehabilitation treadmill.
Step 3 Rotate the support arm backward and lock it.
Step 4 Connect the suspension pull rope with the patient’s weight support vest, control the system to operate the active suspension-based weight support mechanism, and slowly lift the patient to have them stand.
Step 5 Have the patient wear the exoskeleton and lower limbs.
Step 6 Remove the folded wheelchair from the slope to complete the final wearing steps.
Wearing steps of the rehabilitation robot
Appendix 2: calculation environment
See Table 10.
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Li, S., Huang, S., Huang, L. et al. Design and optimization of a body weight support system for lower-limb rehabilitation robots considering vibration characteristics. Struct Multidisc Optim 66, 249 (2023). https://doi.org/10.1007/s00158-023-03700-y
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DOI: https://doi.org/10.1007/s00158-023-03700-y