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Development of a novel unpowered rigid-flexible coupling waist exoskeleton through dynamic dimensional synthesis inspired by biomimetic cooperation

Published online by Cambridge University Press:  02 June 2025

Yuwei Yang ,
Shuo Li Open the ORCID record for Shuo Li [Opens in a new window] ,
Zhaotong Li ,
Zuyi Zhou  and
Jutao Wang
Yuwei Yang
Affiliation:
Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, School of Mechanical Engineering, Tianjin University of Technology, Tianjin, PR China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education, Tianjin University of Technology, Tianjin, PR China
Shuo Li
Affiliation:
Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, School of Mechanical Engineering, Tianjin University of Technology, Tianjin, PR China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education, Tianjin University of Technology, Tianjin, PR China
Zhaotong Li
Affiliation:
Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, School of Mechanical Engineering, Tianjin University of Technology, Tianjin, PR China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education, Tianjin University of Technology, Tianjin, PR China
Zuyi Zhou
Affiliation:
Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, School of Mechanical Engineering, Tianjin University of Technology, Tianjin, PR China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education, Tianjin University of Technology, Tianjin, PR China
Jutao Wang*
Affiliation:
Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, School of Mechanical Engineering, Tianjin University of Technology, Tianjin, PR China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education, Tianjin University of Technology, Tianjin, PR China
*
Corresponding author: Jutao Wang; Email: buddhawei2@126.com
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Abstract

In response to the auxiliary requirements for the treatment and prevention of lumbar diseases, based on the biomechanical characteristics of the human waist, a novel unpowered rigid-flexible coupling waist exoskeleton with multiple degrees of freedom and its human-exoskeleton parallel wearable equivalent research prototype are proposed, further focusing on the encompassing kinematic compatibility and dynamic load-bearing effectiveness of the biomimetic coordination, an in-depth analysis is performed on the multi-body dynamic dimensional synthesis and its methodological research. Initially, based on the rigid-flexible coupling characteristics and experimental biomechanical data of the lumbar region in the sagittal plane, an accurate multi-body system dynamics model of the research prototype, which incorporates the rigid-flexible coupling characteristics, is systematically constructed. Subsequently, to effectively quantify the biomimetic coordination of the exoskeleton, a novel comprehensive optimization index, termed biomimetic load-bearing comfort, is proposed. Finally, by utilizing this index, the exoskeleton is optimized in dimension by employing a thorough combination of multi-dimensional spatial search algorithm and compression factor particle swarm algorithm. The simulation results validate the correctness and effectiveness of both the dynamic dimensional synthesis and its methodology. Furthermore, the study also reveals that the optimized exoskeleton’s passive working mode showcases favorable biomimetic coordination. These results are crucial for progressing the research on the biomimetic load-bearing capacities of other exoskeletons.

Keywords

unpowered waist exoskeletonrigid-flexible couplinghuman-exoskeleton parallel wearable equivalent research prototypebiomimetic cooperationdynamic dimensional synthesis
Type
Research Article
Information
Robotica , First View , pp. 1 - 27
Copyright
© The Author(s) 2025. Published by Cambridge University Press

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References

Zhong, R., Hu, B., Feng, Y., Zheng, H., Hong, Z., Lou, S. and Tan, J., “Construction of human digital twin model based on multimodal data and its application in locomotion mode identification,” Chin. J. Mech. Eng. 36(1), 126–139 (2023).10.1186/s10033-023-00951-0CrossRefGoogle Scholar
Burton, K. and Kendall, N., “Musculoskeletal disorders,” BMJ 348(1), g1076 (2014).CrossRefGoogle ScholarPubMed
Dick, R. B., Lowe, B. D., Lu, M.-L. and Krieg, E. F., “Trends in work-related musculoskeletal disorders from the 2002 to 2014 general social survey, quality of work life supplement,” J. Occup. Environ. Med. 62(8), 595–610 (2020).CrossRefGoogle ScholarPubMed
DeKok, J., Vroonhof, P., Snijders, J., Roullis, G., Clarke, M., Peereboom, K., vanDorst, P. and Isusi, I.. Work-Related Musculoskeletal Disorders: Prevalence, Costs and Demographics in the EU (Publications Office of the European Union, Luxembourg, 2019). https://osha.europa.eu/sites/default/files/Work_related_MSDs_prevalence_costs_and_demographics_in_EU_summary.pdf Google Scholar
Eurostat, Health and Safety at Work in Europe (1999-2007): A Statistical Portrait (The Publications Office of the European Union, Luxembourg, 2010). https://ec.europa.eu/eurostat/web/products-statistical-books/-/KS-31-09-290 Google Scholar
Valirad, F., Ghaffari, M., Abdi, A., Attarchi, M., Mircheraghi, S. F. and Mohammadi, S., “Interaction of physical exposures and occupational factors on sickness absence in automotive industry workers,” Glob. J. Health Sci. 7(6), 276–284 (2015).CrossRefGoogle ScholarPubMed
Sobrepera, M. J., Nguyen, A. T., Gavin, E. S. and Johnson, M. J., “Insights into the deployment of a social robot-augmented telepresence robot in an elder care clinic – perspectives from patients and therapists: A pilot study,” Robotica 42(5), 1321–1349 (2024).CrossRefGoogle Scholar
Wang, T., Zhang, B., Liu, C., Liu, T., Han, Y., Wang, S., Ferreira, J. P., Dong, W. and Zhang, X., “A review on the rehabilitation exoskeletons for the lower limbs of the elderly and the disabled,” Electronics 11(3), 388 (2022).CrossRefGoogle Scholar
Zhang, T. and Huang, H., “A lower-back robotic exoskeleton: Industrial handling augmentation used to provide spinal support,” IEEE Robot Autom Mag. 25(2), 95–106 (2018).CrossRefGoogle Scholar
Arefeen, A. and Xiang, Y., “Artificial neural network-based control of powered knee exoskeletons for lifting tasks: Design and experimental validation,” Robotica 42(9), 2949–2968 (2024).CrossRefGoogle Scholar
Molteni, F., Gasperini, G., Cannaviello, G. and Guanziroli, E., “Exoskeleton and end-effector robots for upper and lower limbs rehabilitation: narrative review,” PM&R 10(9), S174–S188 (2018).Google ScholarPubMed
Arefeen, A. and Xiang, Y., “Subject specific optimal control of powered knee exoskeleton to assist human lifting tasks under controlled environment,” Robotica 41(9), 2809–2828 (2023).CrossRefGoogle Scholar
Masengo, G., Zhang, X., Dong, R., Alhassan, A. B., Hamza, K. and Mudaheranwa, E., “Lower limb exoskeleton robot and its cooperative control: A review, trends, and challenges for future research,” Front. Neurorobot. 16(913748), 1–25  (2023) doi: 10.3389/fnbot.2022.913748.CrossRefGoogle ScholarPubMed
Chae, S., Choi, A., Kang, J. and Mun, J. H., “Can pressure data from wearable insole devices be utilized to estimate low back moments for exoskeleton control system?” Actuators 13(3), 92 (2024). MDPI.CrossRefGoogle Scholar
Pesenti, M., Antonietti, A., Gandolla, M. and Pedrocchi, A., “Towards a functional performance validation standard for industrial low-back exoskeletons: State of the art review,” Sensors 21(3), 808 (2021).CrossRefGoogle ScholarPubMed
Toxiri, S., Näf, M. B., Lazzaroni, M., Fernández, J., Sposito, M., Poliero, T., Monica, L., Anastasi, S., Caldwell, D. G. and Ortiz, J., “Back-support exoskeletons for occupational use: An overview of technological advances and trends,” IISE Trans. Occup. Ergon. Hum. Factors 7(3-4), 237–249 (2019).CrossRefGoogle Scholar
Rosales, I., Lopez, R., Aguilar, H., Rosales, Y. and Lozano, R., “Pneumatic Assistant of One Degree of Freedom for Lifting,” 19th International Conference on System Theory, Control and Computing (ICSTCC), IEEE, Piscataway, NJ (2015) pp. 249–254.Google Scholar
Tanaka, T., Satoh, Y., Kaneko, S., Suzuki, Y., Sakamoto, N and Seki, S., “Smart Suit: Soft Power Suit with Semi-Active Assist Mechanism-Prototype for Supporting Waist and Knee Joint,” International Conference on Control, Automation and Systems, IEEE, Piscataway, NJ (2008) pp. 2002–2005.Google Scholar
Muramatsu, Y., Umehara, H. and Kobayashi, H., “Improvement and Quantitative Performance Estimation of the Back Support Muscle Suit,” 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, Piscataway, NJ (2013) pp. 2844–2849.Google Scholar
Schwartz, M., Desbrosses, K., Theurel, J. and Mornieux, G., “Using passive or active back-support exoskeletons during a repetitive lifting task: Influence on cardiorespiratory parameters,” Eur J Appl Physiol 122(12), 2575–2583 (2022).CrossRefGoogle ScholarPubMed
Ide, M., Hashimoto, T., Matsumoto, K. and Kobayashi, H., “Evaluation of the power assist effect of muscle suit for lower back support,” Quality Control, Transactions 9(1), 3249–3260 (2021).Google Scholar
Hyun, D. J., Lim, H. S., Park, S. I. and Nam, S., “Singular wire-driven series elastic actuation with force control for a waist assistive exoskeleton, H-WEXv2,” IEEE/ASME Trans Mechatron 25(2), 1026–1035 (2020).10.1109/TMECH.2020.2970448CrossRefGoogle Scholar
Tang, Z., Zhang, K., Sun, S., Gao, Z., Zhang, L. and Yang, Z., “An upper-limb power-assist exoskeleton using proportional myoelectric control,” Sensors 14(4), 6677–6694 (2014).CrossRefGoogle ScholarPubMed
Chu, H. R., Chiou, S. J., Li, I. H. and Lee, L. W., “Design, development, and control of a novel upper-limb power-assist exoskeleton system driven by pneumatic muscle actuators,” Actuators 11(8), 231 (2022). MDPI.CrossRefGoogle Scholar
Zuo, J., Liu, Q., Meng, W., Ai, Q. and Xie, S. Q., “Enhanced compensation control of pneumatic muscle actuator with high-order modified dynamic model,” ISA Trans. 132(0019–0578) 1929–1953 (2023).CrossRefGoogle ScholarPubMed
Li, J., He, Y., Sun, J., Li, F., Ye, J., Chen, G., Pang, J. and Wu, X., “Development and evaluation of a lumbar assisted exoskeleton with mixed lifting tasks by various postures,” IEEE Trans Neural Syst Rehabil Eng 32(3707–9423), 2111–2119 (2023) doi: 10.1109/TNSRE.2023.3268657.CrossRefGoogle Scholar
Roberts, S. B. and Chen, P. H., “Elastostatic analysis of the human thoracic skeleton,” J. Biomech. 3(6), 527–545 (1970).10.1016/0021-9290(70)90037-0CrossRefGoogle ScholarPubMed
Shirazi-Adl, A. and Pamianpour, M., “Nonlinear response analysis of the human ligamentous lumbar spine in compression: On mechanisms affecting the postural stability,” Spine 18(1), 147–158 (1993).CrossRefGoogle ScholarPubMed
Panico, M., Bassani, T., Villa, T. M. T. and Galbusera, F., “The simulation of muscles forces increases the stresses in lumbar fixation implants with respect to pure moment loading,” Front. Bioeng. Biotechnol. 9, 745703 (2021). doi: 10.3389/fbioe.2021.745703.CrossRefGoogle ScholarPubMed
Shabana, A. A.. Dynamics of Multibody Systems (Cambridge University Press, Boston, USA and Berlin, Germany, 2020). doi: 10.1017/9781108757553.CrossRefGoogle Scholar
Korayem, M. H., Rahimi, H. N. and Nikoobin, A., “Mathematical modeling and trajectory planning of mobile manipulators with flexible links and joints,” Appl. Math. Model. 36(7), 3229–3244 (2012).10.1016/j.apm.2011.10.002CrossRefGoogle Scholar
Lu, H., Wang, H. and Feng, Y., “Human-machine coupling dynamics modeling and active compliance control of lower limb rehabilitation robot,” J. Mech. Eng. 58(7), 32–43 (2022).Google Scholar
Bazrgari, B., Shirazi-Adl, A. and Parnianpour, M., “Transient analysis of trunk response in sudden release loading using kinematics-driven finite element model,” Clin Biomech 24(4), 341–347 (2009).10.1016/j.clinbiomech.2009.02.002CrossRefGoogle ScholarPubMed
Pearsall, D. J., Reid, J. G. and Livingston, L. A., “Segmental inertial parameters of the human trunk as determined from computed tomography,” Ann. Biomed. Eng. 24(2), 198–210 (1996).CrossRefGoogle ScholarPubMed
Yuwei, Y., Bin, L., Haibo, Z., Xinhua, Z., Yang, S., Liang, L. and Lei, Z., “Dynamic analysis of a mobile parallel manipulator with imperfect kinematic joints,” J. Mech. Eng. 55(15), 208–216 (2019).CrossRefGoogle Scholar
Shabana, A. A.. Computational Dynamics (John Wiley & Sons, Boston, USA and Berlin, Germany, 2009) doi: 10.1002/9780470686850.Google Scholar
Trautt, T. A. and Bayo, E., “Inverse dynamics of flexible manipulators with coulomb friction or backlash and non-zero initial conditions,” Dynam Control 9(2), 173–195 (1999).10.1023/A:1008369813432CrossRefGoogle Scholar
Ping, X. I. E., Yihao, D. U., Peitao, T. and Bin, L. I. U., “A parallel robot error comprehensive compensation method,” J. Mech. Eng. 48(9), 43–49 (2012).Google Scholar
Li, Y., Mei, J., Liu, S. and Huang, T., “Dynamic dimensional synthesis of a 4-DOF high-speed parallel manipulator,” J. Mech. Eng. 50(19), 32–40 (2014).10.3901/JME.2014.19.032CrossRefGoogle Scholar