Hostname: page-component-7b7567c8c-jswmv Total loading time: 0 Render date: 2026-11-15T17:44:57.200Z Has data issue: false hasContentIssue false
  • English
  • Français

Development of nonmotorized mechanisms for lower limb rehabilitation

Published online by Cambridge University Press:  04 May 2021

Rogério S. Gonçalves and
Lucas A. O. RodriguesOpen the ORCID record for Lucas A. O. Rodrigues[Opens in a new window]
Rogério S. Gonçalves
Affiliation:
Faculty of Mechanical Engineering, Federal University of Uberlândia, Uberlândia, Brazil
Lucas A. O. Rodrigues*
Affiliation:
Faculty of Mechanical Engineering, Federal University of Uberlândia, Uberlândia, Brazil
*
*Corresponding author. Email: lucas.ep@outlook.com
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

This paper concerns with the development of three nonmotorized individual lower limb joints rehabilitation mechanisms based on a four-bar linkage, and mechanical movement transmission from the motion of the patient’s upper limb. Initially, mathematical and computational models are built based on the desired angular motions for the hip, knee, and ankle. A prototype for the knee mechanism was constructed for initial experimental tests. The first test with wooden mannequin show that this prototype is lightweight, has an output movement compatible with the amplitudes, is easy to build and operate, being thus ready for clinical tests with healthy and impaired subjects.

Keywords

Closed kinematic chainsGeometrical matrix methodLower limbRehabilitationSingularity analysis

Information

Type
Article
Information
Robotica , Volume 40 , Issue 1 , January 2022, pp. 102 - 119
Copyright
© The Author(s), 2021. Published by Cambridge University Press

References

Oña Simbaña, E. D., Sanchez-Herrera Baeza, P., Jardon Huete, A. and Balaguer, C., “Review of automated systems for upper limbs functional assessment in neurorehabilitation,” IEEE Access 7, 32352–32367 (2019). doi: 10.1109/ACCESS.2019.2901814 CrossRefGoogle Scholar
Hu, W., Li, G., Sun, Y., Jiang, G., Kong, J., Ju, Z. and Jiang, D., “A Review of Upper and Lower Limb Rehabilitation Training Robot,” Intelligent Robotics and Applications (2017) pp. 570–580.Google Scholar
Lum, P., Reinkensmeyer, D., Mahoney, R., Rymer, W. Z. and Burgar, C., “Robotic devices for movement therapy after stroke: Current status and challenges to clinical acceptance,” Top. Stroke Rehabil. 8(4), 40–53 (2002).CrossRefGoogle ScholarPubMed
Lackland, D., Heart Disease and Stroke Statistics 2017 Update A Report From the American Heart Association (2017).Google Scholar
Diaz, I., Gil, J. J. and Sanchez, E., “Lower-limb robotic rehabilitation: Literature review and challenges,” J. Rob. 2011(11), e759764 (2011).Google Scholar
Esquenazi, A. and Talaty, M., “Robotics for lower limb rehabilitation”, Phys. Med. Rehabil. Clin. North Am. 30(2), 385–397 (2019). doi: 10.1016/j.pmr.2018.12.012 CrossRefGoogle ScholarPubMed
Wang, H., Li, W., Liu, H., Zhang, J. and Liu, S., “Conceptual design and dimensional synthesis of a novel parallel mechanism for lower-limb rehabilitation,” Robotica 37(3), 469–480 (2019). doi: 10.1017/S0263574718001121 CrossRefGoogle Scholar
Cafolla, D., Russo, M. and Carbone, G., “CUBE, a cable-driven device for limb rehabilitation,” J. Bionic Eng. 16(3), 492–502 (2019). doi: 10.1007/s42235-019-0040-5 CrossRefGoogle Scholar
Viteckova, S., Kutilek, P., de Boisboissel, G., Krupicka, R., Galajdova, A., Kauler, J., Lhotska, L. and Szabo, Z., “Empowering lower limbs exoskeletons: State-of-the-art,” Robotica 36(11), 1743–1756 (2018). doi: 10.1017/S0263574718000693 CrossRefGoogle Scholar
Sales Gonçalves, R., Soares, G. and Carvalho, J. C., “Conceptual design of a rehabilitation device based on cam-follower and crank-rocker mechanisms hand actioned,” J. Brazilian Soc. Mech. Sci. Eng. 41(3), 277 (2019).CrossRefGoogle Scholar
Lo, K., Stephenson, M. and Lockwood, C., “The economic cost of robotic rehabilitation for adult stroke patients: a systematic review,” JBI Database Syst. Rev. Implementation Rep. 17(4), 520–547 (2019). doi: 10.11124/JBISRIR-2017-003896 CrossRefGoogle ScholarPubMed
Shao, Y., Xiang, Z., Liu, H. and Li, L., “Conceptual design and dimensional synthesis of cam-linkage mechanisms for gait rehabilitation,” Mech. Mach. Theory 104(2016), 31–42 (2016).CrossRefGoogle Scholar
Stienen, A., Hekman, E. E. G., van der Helm, F., Prange, G., Jannink, M., Aalsma, A. and Kooij, H., “Dampace: Dynamic Force-Coordination Trainer for the Upper Extremities,” 2007 IEEE 10th International Conference on Rehabilitation Robotics, (c) (2007) pp. 820–826.Google Scholar
Sanchez, R. J., Liu, J., Rao, S., Shah, P., Smith, R., Rahman, T., Cramer, S. C., Bobrow, J. E. and Reinkensmeyer, D. J., “Automating arm movement training following severe stroke: Functional exercises with quantitative feedback in a gravity-reduced environment,” IEEE Trans. Neural Syst. Rehabil. Eng. 14(3), 378–389 (2006).CrossRefGoogle Scholar
Cho, K. H. and Song, W.-K., “Feedback training using a non-motorized device for longterm upper extremity impairment after stroke: a single group study,” J. Phys. Ther. Sci. 28(2), 495–499 (2016).CrossRefGoogle ScholarPubMed
Sasada, S., Tazoe, T., Nakajima, T., Futatsubashi, G., Ohtsuka, H., Suzuki, S., Paul Zehr, E. and Komiyama, T., “A common neural element receiving rhythmic arm and leg activity as assessed by reflex modulation in arm muscles,” J. Neurophysiol. 115(4), 2065–2075 (2016).CrossRefGoogle ScholarPubMed
Balter, J. E. and Zehr, E. P., “Neural coupling between the arms and legs during rhythmic locomotor-like cycling movement,” J. Neurophysiol. 97(2), 1809–1818 (2007).CrossRefGoogle ScholarPubMed
Huang, H. J. and Ferris, D. P., “Neural coupling between upper and lower limbs during recumbent stepping,” J. Appl. Physiol. 97(4), 1299–1308 (2004).CrossRefGoogle ScholarPubMed
Klarner, T., Barss, T. S., Sun, Y., Kaupp, C., Loadman, P. M. and Zehr, E. P., “Exploiting interlimb arm and leg connections for walking rehabilitation: A training intervention in stroke,” Neural Plast. 2016 (2016). Article ID 1517968. doi: 10.1155/2016/1517968 CrossRefGoogle Scholar
Kaupp, C., “Rhythmic Arm Cycling Training Improves Walking and Interlimb Integrity in Chronic Stroke Master Thesis (University of Victoria, 2018) p. 105.Google Scholar
Zehr, E. P., Balter, J. E., Ferris, D. P., Hundza, S. R., Loadman, P. M. and Stoloff, R. H., “Neural regulation of rhythmic arm and leg movement is conserved across human locomotor tasks,” J. Physiol. 582(1), 209–227 (2007).CrossRefGoogle ScholarPubMed
Gonçalves, R. S., Carvalho, J. C. M., Ribeiro, J. F. and Salim, V. V., “Cable-driven robot for upper and lower limbs rehabilitation,” Handb. Res. Adv. Rob. Mechatron. 2015, 284–315 (2014). doi: 10.4018/978-1-4666-7387-8.ch011 CrossRefGoogle Scholar
Barbosa, A. M., Carvalho, J. C. M. and Gonçalves, R. S., “Cable-driven lower limb rehabilitation robot,” J. Braz. Soc. Mech. Sci. Eng. 40(5), 1–11 (2018). Article ID 245.CrossRefGoogle Scholar
Gonçalves, R. S., Carvalho, J. C. M., Rodrigues, L. A. O. and Barbosa, A. M., “Cable-driven parallel manipulator for lower limb rehabilitation,” Appl. Mech. Mater. 459, 535–542 (2013). doi: 10.4028/www.scientific.net/amm.459.535 CrossRefGoogle Scholar
Alves, T., Chaves D’Carvalho, M. and Sales Gonçalves, R., “Assist-as-needed control in a cable-actuated robot for human joints rehabilitation,” J. Mech. Eng. Biomech. 3(5), 57–62 (2019).CrossRefGoogle Scholar
Gonalves, R. S., Carvalho, J. C. M. and Lobato, F. S., “Design of a robotic device actuated by cables for human lower limb rehabilitation using self-adaptive differential evolution and robust optimization,” Biosci. J. 32(6), 1689–1702 (2016).CrossRefGoogle Scholar
Gonalves, R. S. and Rodrigues, L. A. O., “Development of a Novel Parallel Structure for Gait Rehabilitation,” In: Handbook of Research on Advanced Mechatronic Systems and Intelligent Robotics (2019) p. 4281.Google Scholar
Bateni, H. and Maki, B. E., “Assistive devices for balance and mobility: Benefits, demands, and adverse consequences,” Arch. Phys. Med. Rehabil. 86(1), 134–145 (2005).CrossRefGoogle ScholarPubMed
Kapandji, I., Physiology of the Joints: Lower Limb, 6th ed. (Churchill Livingstone, London, 2010).Google Scholar
Uicker, J. J., Pennock, G. R., Shigley, J. E. and McCarthy, J. M., “Theory of machines and mechanisms,” J. Mech. Des. 125(3), 650 (2003).Google Scholar
Lobato, F. S., Steffen, V. Jr and Oliveira-Lopes, L. C., “An Evolutionary Approach Based on Search Chaotic Pattern Associated to Differential Evolution Algorithm,” 17 ° Simpísio do Programa de Pós-graduação em Engenharia Mecânica (2007) p. 9.Google Scholar
Clauser, C. E., McConville, J. T., Young, J. W. and Clauser, C. E., Weight, Volume and Center of Mass of Segments of the Human Body. AMRL Technical Report, Wright Patterson Air Force Base, Ohio (1969) pp. 101.Google Scholar
IBGE - Instituto Brasileiro de Geografia e Estatística, Antropometria e Estado Nutricional no Brasil 2008–2009 (2010).Google Scholar
Handbook Committee, ASM, Properties and Selection: Nonferrous Alloys and Special-Purpose Materials (ASM International, 2007). doi: 10.31399/asm.hb.v02.9781627081627 Google Scholar
Neumann, D., Kinesiology of The Musculoskeletal System (Elsevier B.V., 2010).Google Scholar
Zlatanov, D. S., Generalized Singularity Analysis of Mechanisms (University of Toronto, 1998).Google Scholar
Altuzarra, O., Pinto, C., Avilés, R. and Hernández, A., “A practical procedure to analyze singular configurations in closed kinematic chains,” IEEE Trans. Robot. 20(6), 929–940 (2004).CrossRefGoogle Scholar
Altuzarra, O., Salgado, O., Petuya, V. and Hernández, A., “Point-based Jacobian formulation for computational kinematics of manipulators,” Mech. Mach. Theory 41(12), 1407–1423 (2006).CrossRefGoogle Scholar
Hernández, A., Altuzarra, O., Avilés, R. and Petuya, V., “Kinematic analysis of mechanisms via a velocity equation based in a geometric matrix,” Mech. Mach. Theory 38(12), 1413–1429 (2003).CrossRefGoogle Scholar