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8 Degrees of freedom human lower extremity kinematic and dynamic model development and control for exoskeleton robot based physical therapy

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Abstract

The World Health Organization reports that approximately 15% of the world’s population is disabled. Physiotherapy helps promote functional recovery in upper and lower extremity impairment. An exoskeleton robot-based exercise tool for neurorehabilitation is an appealing solution to treat many disabled people. Knowledge of anatomical characteristics and anthropometrical properties are equally important for mechanical design, as well as modeling, and control of exoskeleton robots. However, most of the anthropometrical data is not readily available from a single source. Additionally, eight degrees of freedom human lower extremity kinematic and dynamic models are also not available. This paper presents dynamic modeling and simulation of the human lower extremity (HLE). A comprehensive review of HLE anatomical characteristics, degrees of freedom, and range of motion of various joints are presented. The Lagrange energy method is used for developing the dynamic model. The developed model includes both linear and rotational displacements of the knee joint. The dynamic simulation uses a sliding mode controller. Simulation results show the performance of the controller, joint torque, and power requirements for tracking specified trajectories. It is also shown that sliding mode control (SMC) is a robust control scheme that works effectively even in the presence of external disturbances and parameter variations. The simulation results indicate that SMC is a suitable choice for controlling a physical exoskeleton robot.

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References

  1. Organization WH (2015) WHO global disability action plan 2014–2021: better health for all people with disability. World Health Organization, Geneva

    Google Scholar 

  2. Heidenreich PA, Trogdon JG, Khavjou OA, Butler J, Dracup K, Ezekowitz MD, Finkelstein EA, Hong Y, Johnston SC, Khera A, Lloyd-Jones DM, Nelson SA, Nichol G, Orenstein D, Wilson PWF, Woo YJ (2011) Forecasting the future of cardiovascular disease in the United States. Circulation 123(8):933–944

    Article  Google Scholar 

  3. Prange GB, Jannink MJ, Groothuis-Oudshoorn CG, Hermens HJ, Ijzerman MJ (2006) Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. J Rehabil Res Dev 43(2):171–184

    Article  Google Scholar 

  4. Kong K, Moon H, Hwang B, Jeon D, Tomizuka M (2009) Impedance compensation of SUBAR for back-drivable force-mode actuation. IEEE Trans Robot 25(3):512–521

    Article  Google Scholar 

  5. Lunenburger L, Colombo G, Riener R, Dietz V (2005) Clinical assessments performed during robotic rehabilitation by the gait training robot Lokomat. In: 9th international conference on rehabilitation robotics. ICORR 2005. pp 345–348

  6. Kawamoto H, Sankai Y (2004) Power assist method based on phase sequence driven by interaction between human and robot suit. In: RO-MAN 2004. 13th IEEE international workshop on robot and human interactive communication (IEEE Catalog No. 04TH8759). pp 491–496

  7. Goffer A (2006) Gait-locomotor apparatus. US Patent 7,153,242

  8. Farris RJ, Quintero HA, Murray SA, Ha KH, Hartigan C, Goldfarb M (2014) A preliminary assessment of legged mobility provided by a lower limb exoskeleton for persons with paraplegia. IEEE Trans Neural Syst Rehabil Eng 22(3):482–490

    Article  Google Scholar 

  9. Sanz-Merodio D, Cestari M, Arevalo JC, Garcia E (2012) Control motion approach of a lower limb orthosis to reduce energy consumption. Int J Adv Robot Syst 9(6):232

    Article  Google Scholar 

  10. Neuhaus PD, Noorden JH, Craig TJ, Torres T, Kirschbaum J, Pratt JE (2011) Design and evaluation of Mina: a robotic orthosis for paraplegics. In: 2011 IEEE international conference on rehabilitation robotics. pp 1–8

  11. Kiguchi K, Iwami K, Yasuda M, Watanabe K, Fukuda T (2003) An exoskeletal robot for human shoulder joint motion assist. IEEE ASME Trans Mechatron 8(1):125–135

    Article  Google Scholar 

  12. Kagawa T, Uno Y (2009) Gait pattern generation for a power-assist device of paraplegic gait. In: RO-MAN 2009—The 18th IEEE international symposium on robot and human interactive communication. pp 633–638

  13. Ekkelenkamp R, Veneman J, Kooij (2005) Hvd LOPES: selective control of gait functions during the gait rehabilitation of CVA patients. In: ICORR 2005. 9th international conference on rehabilitation robotics. pp 361–364

  14. Banala SK, Agrawal SK, Scholz JP (2007) Active leg exoskeleton (ALEX) for gait rehabilitation of motor-impaired patients. In: 2007 IEEE 10th international conference on rehabilitation robotics. pp 401–407

  15. Strickland E (2011) Good-bye, Wheelchair, Hello Exoskeleton. IEEE SPECTRUM. http://spectrum.ieee.org/biomedical/bionics/goodbye-wheelchair-hello-exoskeleton. Accessed 21 May 2019

  16. Wang L, Wang S, Asseldonk EHFV, Kooij HVD (2013) Actively controlled lateral gait assistance in a lower limb exoskeleton. In: 2013 IEEE/RSJ international conference on intelligent robots and systems. pp 965–970

  17. Gloger M, Alsina PJ, Melo NB (2015) Ortholeg 2.0—a new design for a lower limb active orthosis. In: 2015 International symposium on micro-nanomechatronics and human science (MHS). pp 1–7

  18. Kim J-H, Han JW, Kim DY, Baek YS (2013) Design of a walking assistance lower limb exoskeleton for paraplegic patients and hardware validation using CoP. Int J Adv Robot Syst 10(2):113

    Article  Google Scholar 

  19. Hian Kai K, Noorden JH, Missel M, Craig T, Pratt JE, Neuhaus PD (2009) Development of the IHMC mobility assist exoskeleton. In: 2009 IEEE international conference on robotics and automation. pp 2556–2562

  20. Kawamoto H, Hayashi T, Sakurai T, Eguchi K, Sankai Y (2009) Development of single leg version of HAL for hemiplegia. In: 2009 Annual international conference of the ieee engineering in medicine and biology society. pp 5038–5043

  21. Cenciarini M, Dollar AM (2011) Biomechanical considerations in the design of lower limb exoskeletons. In: 2011 IEEE International conference on rehabilitation robotics. pp 1–6

  22. Farris RJ, Hugo AQ, Murray S, Ha KH, Hartigan C, Goldfarb M (2014) A preliminary assessment of legged mobility provided by a lower limb exoskeleton for persons with paraplegia. IEEE Trans Neural Syst Rehabil Eng 22:482–490

    Article  Google Scholar 

  23. Munawar H, Yalcin M, Patoglu V (2015) AssistOn-Gait: an overground gait trainer with an active pelvis-hip exoskeleton. In: 2015 IEEE International conference on rehabilitation robotics (ICORR). pp 594–599

  24. Apkarian J, Naumann S, Cairns B (1989) A three-dimensional kinematic and dynamic model of the lower limb. J Biomech 22(2):143–155

    Article  Google Scholar 

  25. Yan LJ, Shen QM, Yang D, Qiao JM, Datseris P (2019) Kinematic and dynamic modeling and analysis of a lower extremity exoskeleton. In: 2019 16th International conference on ubiquitous robots (UR). pp 625–630

  26. Kazerooni H, Steger R, Huang L (2006) Hybrid control of the berkeley lower extremity exoskeleton (BLEEX). Int J Robot Res 25(5–6):561–573

    Article  Google Scholar 

  27. Moosavian SAA, Nabipour M, Absalan F, Akbari V (2019) RoboWalk: explicit augmented human-robot dynamics modeling for design optimization. arXiv e-prints: arXiv:1907.04114

  28. Sartori M, Reggiani M, Farina D, Lloyd DG (2012) EMG-driven forward-dynamic estimation of muscle force and joint moment about multiple degrees of freedom in the human lower extremity. PLoS ONE 7(12):e52618

    Article  Google Scholar 

  29. Baluch TH, Masood A, Iqbal J, Izhar U, Khan US (2012) Kinematic and dynamic analysis of a lower limb exoskeleton. Int J Mech Mechatron Eng 6(9):1945–1949

    Google Scholar 

  30. Russell F, Vaidyanathan R, Ellison P (2018) A kinematic model for the design of a bicondylar mechanical knee. In: 2018 7th IEEE international conference on biomedical robotics and biomechatronics (Biorob). pp 750–755

  31. Surgeons AAOO (1965) Joint motion: methods of measuring and recording. American Academy of Orthopaedic Surgeons, Chicago

    Google Scholar 

  32. Kendall FP, McCreary EK, Provance PG, Rodgers MM, Romani WA (2005) Muscles: testing and function, with posture and pain, 5th edn. LWW, Philadelphia

    Google Scholar 

  33. Kurz T (2015) Normal ranges of joint motion. http://web.mit.edu/tkd/stretch/stretching_8.html. Accessed 06 Apr 2019

  34. Nikolova G, Toshev Y (2008) Comparison of two approaches for calculation of the geometric and inertial characteristics of the human body of the Bulgarian population. Acta Bioeng Biomech 10(1):3–8

    Google Scholar 

  35. Contini R (1972) Body segment parameters, part I I. Artif Limbs 16(1):1–19

    Google Scholar 

  36. Blanco JL (2019) Mobile robot programming toolkit (MRPT). https://www.mrpt.org/. Accessed 12 Sept 2019

  37. Morin DJ (2014) Problems and solutions in introductory mechanics, 1st edn. CreateSpace, Scotts Valley

    Google Scholar 

  38. Utkin V (2011) Chattering problem. IFAC Proc 44(1):13374–13379

    Article  Google Scholar 

  39. Utkin VI (1993) Sliding mode control design principles and applications to electric drives. IEEE Trans Ind Electron 40(1):23–36

    Article  Google Scholar 

  40. Xu R, Zhou M (2017) Sliding mode control with sigmoid function for the motion tracking control of the piezo-actuated stages. Electron Lett 53:75–77

    Article  Google Scholar 

  41. Cheng NB, Guan LW, Wang LP, Han J (2011) Chattering reduction of sliding mode control by adopting nonlinear saturation function. Adv Mater Res 143–144:53–61

    Google Scholar 

  42. Pan Y, Yang C, Pan L, Yu H (2018) Integral sliding mode control: performance, modification, and improvement. IEEE Trans Industr Inf 14(7):3087–3096

    Article  Google Scholar 

  43. Shtessel Y, Fridman L, Zinober A (2008) Higher-order sliding modes. Int J Robust Nonlinear Control 18:381–384

    Article  MathSciNet  Google Scholar 

  44. Rivera Dominguez J, Garcia L, Mora C, Panduro J, Ortega S (2011) Super-twisting sliding mode in motion control systems. In: Bartoszewicz A (ed) Sliding mode control. IntechOpen, London, pp 237–254

    Google Scholar 

  45. Inoue T, Nakano M, Iwai S High accuracy control of servomechanism for repeated contouring. In: 10th Annual symposium on incremental motion control systems and devices. Urbana-Champaign. pp 285–292

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Authors and Affiliations

  1. Department of Mechanical Engineering, University of Wisconsin Milwaukee, Milwaukee, WI, 53211, USA

    SK Hasan & Anoop K. Dhingra

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  1. SK Hasan
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  2. Anoop K. Dhingra
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Correspondence to SK Hasan.

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Hasan, S., Dhingra, A.K. 8 Degrees of freedom human lower extremity kinematic and dynamic model development and control for exoskeleton robot based physical therapy. Int. J. Dynam. Control 8, 867–886 (2020). https://doi.org/10.1007/s40435-020-00620-3

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  • DOI: https://doi.org/10.1007/s40435-020-00620-3

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