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The effect of the 2-UPS/RR ankle rehabilitation robot with coupling biomechanical model on muscle behaviors

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Abstract

With the popularization of biomechanical simulation technology, aiming at the rehabilitation of ankle joint injury, we imported simplified model of proposed 2-UPS/RR (two identical unconstraint kinematic branches with a universal–prismatic–spherical (UPS) structure and two rotating pair (R)) ankle rehabilitation robot into AnyBody Modeling System. Therefore, a human–machine model was established using the HILL-type muscle model and muscle recruitment criteria. This paper investigated the effects of rehabilitation trajectories on biomechanical response during rehabilitation. Additionally, three main lower limb muscles (soleus, peroneal brevis, and extensor digitorum longus) were examined under different rehabilitation trajectories (plantar dorsiflexion, varus or valgus, and compound movement) in the present study. Based on the biomechanical response of lower limbs, the results showed that different muscles had different sensitivities to the change of rehabilitation trajectories. The correlation coefficient between joint force and plantar dorsiflexion angle reached 0.99 (P < 0.01), indicating that the change of joint force was mainly dominated by plantar dorsiflexion/plantar flexion, but also affected by varus or valgus. Safe rehabilitation training can be achieved by controlling the designed 2-UPS/RR rehabilitation robot. The behavior of muscle force and joint force under different rehabilitation trajectories can meet the needs of rehabilitation and treatment of joint diseases, and provide more reasonable suggestions for early rehabilitation.

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References

  1. Van Houcke J, Schouten A, Steenackers G et al (2017) Computer-based estimation of the hip joint reaction force and hip flexion angle in three different sitting configurations[J]. Appl Ergon 63:99–105

    Article  Google Scholar 

  2. Hazrati E, Azghani MR (2018) The effect of saddle height and saddle position changes from pedal on muscles and joints behaviors in ergometer: a parametric study[J]. Proc Inst Mech Eng [H] 232(12):1219–1229

    Article  Google Scholar 

  3. Rajagopal A, Dembia C, Demers MS et al (2016) Full-body musculoskeletal model for muscle-driven simulation of human gait[J]. IEEE Trans Biomed Eng 63(10):2068–2079

    Article  Google Scholar 

  4. Hamner SR, Seth A, Delp SL (2010) Muscle contributions to propulsion and support during running[J]. J Biomech 43(14):2709–2716

    Article  Google Scholar 

  5. Zongxing L, Xiangwen W, Shengxian Y (2020) The effect of sitting position changes from pedaling rehabilitation on muscle activity[J]. Computer Methods in Biomechanics and Biomedical Engineering, 1–10

  6. Fenfang Z, Zhu G, Tsoi Y H, et al (2014) A computational biomechanical model of the human ankle for development of an ankle rehabilitation robot[C]//2014 IEEE/ASME 10th International Conference on Mechatronic and Embedded Systems and Applications (MESA). IEEE, 1–6

  7. Shi M, Yang C, Zhang D (2021) A novel human-machine collaboration model of an ankle joint rehabilitation robot driven by EEG signals[J]. Mathematical Problems in Engineering, 2021

  8. Wang Y, Mei Z, Xu J, et al (2012) Kinematic design of a parallel ankle rehabilitation robot for sprained ankle physiotherapy[J]. Advanced ence Letters 1643 - 1649

  9. Dai JS, Zhao T, Nester C (2004) Sprained ankle physiotherapy based mechanism synthesis and stiffness analysis of a robotic rehabilitation device[J]. Auton Robot 16(2):207–218

    Article  Google Scholar 

  10. Jamwal PK, Xie SQ, Tsoi YH et al (2010) Forward kinematics modelling of a parallel ankle rehabilitation robot using modified fuzzy inference[J]. Mech Mach Theory 45(11):1537–1554

    Article  Google Scholar 

  11. Saglia JA, Tsagarakis NG, Dai JS et al (2009) A high-performance redundantly actuated parallel mechanism for ankle rehabilitation[J]. Int J Robot Res 28(9):1216–1227

    Article  Google Scholar 

  12. Pai DK (2010) Muscle mass in musculoskeletal models[J]. J Biomech 43(11):2093–2098

    Article  Google Scholar 

  13. Adam Siemienski (1989) Soft saturation, an idea for load sharing between muscles. Application to the study of human locomotion[C]// Biolocomotion: A Century of Research Using Moving Pictures

  14. Zajac FE (1989) Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control[J]. Crit Rev Biomed Eng 17(4):359–411

    CAS  Google Scholar 

  15. Sartori M, Reggiani M, Lloyd DG, et al (2011) A neuromusculoskeletal model of the human lower limb: towards EMG-driven actuation of multiple joints in powered orthoses[C]// IEEE International Conference on Rehabilitation Robotics. Beijing,China IEEE

  16. Terada M, Pietrosimone BG, Gribble PA (2013) Therapeutic interventions for increasing ankle dorsiflexion after ankle sprain: a systematic review[J]. J Athletic Train 48(5):696–709

    Article  Google Scholar 

  17. Pontonnier C, De Zee M, Samani A et al (2014) Strengths and limitations of a musculoskeletal model for an analysis of simulated meat cutting tasks [J]. Appl Ergon 45(3):592–600

    Article  Google Scholar 

  18. Dupré T, Dietzsch M, Komnik I et al (2019) Agreement of measured and calculated muscle activity during highly dynamic movements modelled with a spherical knee joint [J]. J Biomech 84:3–80

    Article  Google Scholar 

  19. Dubowsky SR, Rasmussen J, Sisto SA et al (2008) Validation of a musculoskeletal model of wheelchair propulsion and its application to minimizing shoulder joint forces [J]. J Biomech 41(14):2981–2988

    Article  Google Scholar 

  20. Yao L G, Liao Z W, Lu Z X, et al (2018) Nutation motion based trajectory planning for a novel hybrid ankle rehabilitation device[J]. J Mech Eng (online publishing), 1–8

  21. Zhang M, Claire Davies T (2013) Effectiveness of robot-assisted therapy on ankle rehabilitation – a systematic review[J]. J Neuro Eng Rehabilitation 10(1):30–38

    CAS  Google Scholar 

  22. Li J, Zhang Z, Tao C et al (2017) A number synthesis method of the self-adapting upper-limb rehabilitation exoskeletons[J]. Int J Adv Rob Syst 14(3):1729881417710796

    Google Scholar 

  23. Zhou Z, Zhou Y, Wang N, et al (2014) On the design of a robot-assisted rehabilitation system for ankle joint with contracture and/or spasticity based on proprioceptive neuromuscular facilitation[C]// 2014 IEEE International Conference on Robotics and Automation (ICRA 2014), Hong Kong, China 31 May -7 June 2014

  24. Wang C, Fang Y, Guo S et al (2013) Design and kinematical performance analysis of a 3-RUS/R RR redundantly actuated parallel mechanism for ankle rehabilitation[J]. J Mech Robot 5(4):041003

    Article  Google Scholar 

  25. Erdogan A, Celebi B, Satici AC et al (2017) Assist on-ankle: a reconfigurable ankle exoskeleton with series-elastic actuation[J]. Auton Robot 41(3):743–758

    Article  Google Scholar 

  26. Zhang L, Li J, Dong M, et al (2019) Design and workspace analysis of a parallel ankle rehabilitation robot (PARR)[J]. Journal of healthcare engineering, 2019

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Funding

The authors would like to thank the financial support from the National Natural Science Foundation of China (grant no. 61801122).

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Correspondence to Lu Zongxing.

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For this type of study, formal consent is not required. The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the institutional review board of the School of Mechanical Engineering and Automation of Fuzhou University (202108

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Shengxian, Y., Zongxing, L., Jing, W. et al. The effect of the 2-UPS/RR ankle rehabilitation robot with coupling biomechanical model on muscle behaviors. Med Biol Eng Comput 61, 421–434 (2023). https://doi.org/10.1007/s11517-022-02704-y

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  • DOI: https://doi.org/10.1007/s11517-022-02704-y

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