Interaction models between humans and lower-limbs exoskeletons applied to robotic neurorehabilitation
Resumo
Development of interaction controls applied to robots of robotic-assisted therapy is a challenge, as it requires physical contact between human and robots, in addition to demanding a high cost of time and resources. The purpose of this work was to develop a human-exoskeleton interaction model and a simulation algorithm for development, validation and testing of interaction controls applied in robotic rehabilitation of lower-limbs. Two simulations with different interaction models and controls were run, combining experimental and computational data. The results obtained proved that both the interaction model and the simulation algorithm are feasible, useful, improving flexibility and agility for developing of interaction controls.
Palavras-chave:
Robots for robotic surgery and rehabilitation
Referências
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dos Santos, W. M., Caurin, G. A. P., and Siqueira, A. A. G. (2017a). Design and control of an active knee orthosis driven by a rotary series elastic actuator. Control Engineering Practice, 58:307–318.
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Nunes, P. F., dos Santos, W. M., and Siqueira, A. A. G. (2018). Control strategy based on kinetic motor primitives for lower limbs exoskeletons. In 10th IFAC Symposium on Biological and Medical Systems. International Federation of Automatic Control.
NUNES, P. F., SANTOS, W. M., NOGUEIRA, S., and SIQUEIRA, A. A. G. (2017). Analyzing motor primitives of healthy subjects wearing a lower limb exoskeleton. In International Congress of Mechanical Engineering – COBEM, volume 1, Curitiba.
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Peña, G. G., Consoni, L. J., dos Santos, W. M., and Siqueira, A. A. G. (2019). Feasibility of an optimal emg-driven adaptive impedance control applied to an active knee orthosis. Robotics and Autonomous Systems, (112):98–108.
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Rangel, E. S. S., Belasco, A. G. S., and Diccini, S. (2013). Quality of life of patients with stroke rehabilitation. Acta Paulista de Enfermagem, 26(2):205–212.
SAFANELLI, J., VIEIRA, L. G. D. R., de ARAUJO, T., MANCHOPE, L. F. S., KUHLHOFF, M. H. R., NAGEL, V., CONFORTO, A. B., SILVA, G. S., MAZIN, S., de MAGALHÃES, P. S. C., and CABRAL, N. L. (2019). The cost of stroke in a public hospital in brazil: a one-year prospective study. Arquivos de Neuro-Psiquiatria, 77(6):404–411.
Seth, A., Hicks, J. L., Uchida, T. K., Habib, A., Dembia, C. L., Dunne, J. J., Ong, C. F., DeMers, M. S., Rajagopal, A., Millard, M., Hamner, S. R., Arnold, E. M., Yong, J. R., Lakshmikanth, S. K., Sherman, M. A., Ku, J. P., and Delp, S. L. (2018). OpenSim: Simulating musculoskeletal dynamics and neuromuscular control to study human and animal movement. PLOS Computational Biology, 14(7):e1006223.
Trinler, U., Schwameder, H., Baker, R., and Alexander, N. (2019). Muscle force estimation in clinical gait analysis using AnyBody and OpenSim. Journal of Biomechanics, 86:55–63.
WHO (2011). World health organization - world report on disability.
WHO (2018). World health organization - the top 10 causes of death.
Wolpert, D. M., Miall, R. C., and Kawato, M. (1998). Internal models in the cerebellum. Trends in Cognitive Sciences, 2(9):338–347.
Androwis, G. J., Pikar, R., Ramanujam, A., and Nolan, K. J. (2018). Electromyography assessment during gait in a robotic exoskeleton for acute stroke. Frontiers in Neurology, 9:630.
Bayon, C., Fricke, S. S., Rocon, E., van der Kooij, H., and van Asseldonk, E. H. F. (2018). Performance-based adaptive assistance for diverse subtasks of walking in a robotic gait trainer: Description of a new controller and preliminary results. In 2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob), pages 414–419, Enschede, The Netherlands.
Damsgaard, M., Rasmussen, J., Christensen, S. T., Surma, E., and de Zee, M. (2006). Analysis of musculoskeletal systems in the AnyBody modeling system. Simulation Modelling Practice and Theory, 14(8):1100–1111.
de Sousa, A. C. C., Freire, J. P. C. D., and Bo, A. P. L. (2019). Integrating hip exosuit and FES for lower limb rehabilitation in a simulation environment. IFAC-PapersOnLine, 51(34):302–307.
de Sousa, A. C. C., Ramos, F. M., Dorado, M. C. N., Fonseca, L. O., and Bo, A. P. L. ´ (2016). A comparative study on control strategies for fes cycling using a detailed musculoskeletal model. IFAC-PapersOnline, pages 204–209.
Delp, S., Loan, J., Hoy, M., Zajac, F., Topp, E., and Rosen, J. (1990). An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures. IEEE Transactions on Biomedical Engineering, 37(8):757–767.
Delp, S. L., Anderson, F. C., Arnold, A. S., Loan, P., Habib, A., John, C. T., Guendelman, E., and Thelen, D. G. (2007). Opensim: Open-source software to create and analyze dynamic simulations of movement. IEEE Transactions on Biomedical Engineering, 54(11):1940–1950.
Diaz, I., Gil, J. J., and Sanchez, E. (2011). Lower-limb robotic rehabilitation: Literature review and challenges. Journal of Robotics, 2011.
dos Santos, W. M., Caurin, G. A. P., and Siqueira, A. A. G. (2017a). Design and control of an active knee orthosis driven by a rotary series elastic actuator. Control Engineering Practice, 58:307–318.
dos Santos, W. M., Nogueira, S. L., de Oliveira, G. C., Pena, G. G., and Siqueira, A. A. G. (2017b). Design and evaluation of a modular lower limb exoskeleton for rehabilitation. In 2017 International Conference on Rehabilitation Robotics (ICORR). IEEE.
Frey, S. H., Fogassi, L., Grafton, S., Picard, N., Rothwell, J. C., Schweighofer, N., Corbetta, M., and Fitzpatrick, S. M. (2011). Neurological principles and rehabilitation of action disorders. Neurorehabilitation and Neural Repair, 25(5):6–20.
Guzmán, C. H., Blanco, A., Brizuela, J. A., and Gómez, F. A. (2017). Robust control of a hip–joint rehabilitation robot. Biomedical Signal Processing and Control, 35:100–109.
Handford, M. L. and Srinivasan, M. (2018). Energy-optimal human walking with feedback-controlled robotic prostheses: A computational study. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(9):1773–1782.
Jutinico, A. L., Escalante, F. M., Jaimes, J. C., Terra, M. H., and Siqueira, A. A. G. (2018). Markovian robust compliance control based on electromyographic signals. In 2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob), Enschede, The Netherlands.
Jutinico, A. L., Jaimes, J. C., Escalante, F. M., Perez-Ibarra, J. C., Terra, M. H., and Siqueira, A. A. G. (2017). Impedance control for robotic rehabilitation: A robust markovian approach. Frontiers in Neurorobotics, 11:43.
Kainz, H., Modenese, L., Lloyd, D., Maine, S., Walsh, H., and Carty, C. (2016). Joint kinematic calculation based on clinical direct kinematic versus inverse kinematic gait models. Journal of Biomechanics, 49(9):1658–1669.
Khamar, M. and Edrisi, M. (2018). Designing a backstepping sliding mode controller for an assistant human knee exoskeleton based on nonlinear disturbance observer. Mechatronics, 54:121–132.
Kim, J. and Kim, J. (2018). An impedance control of human ankle joint using functional electrical stimulation. In 2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob), pages 1230–1235, Enschede, The Netherlands.
Mackay, J. and Mensah, G. A. (2004). The Atlas of Heart Disease and Stroke. World Health Organization.
Mansouri, M. and Reinbolt, J. A. (2012). A platform for dynamic simulation and control of movement based on opensim and matlab. Journal of biomechanics, 45:1517–21.
Michaud, B. and Begon, M. (2021). biorbd: A c++, python and MATLAB library to analyze and simulate the human body biomechanics. Journal of Open Source Software, 6(57):2562.
MS (2018). Ministerio da saúde - panorama do avc no brasil.
Nunes, P. F., dos Santos, W. M., and Siqueira, A. A. G. (2018). Control strategy based on kinetic motor primitives for lower limbs exoskeletons. In 10th IFAC Symposium on Biological and Medical Systems. International Federation of Automatic Control.
NUNES, P. F., SANTOS, W. M., NOGUEIRA, S., and SIQUEIRA, A. A. G. (2017). Analyzing motor primitives of healthy subjects wearing a lower limb exoskeleton. In International Congress of Mechanical Engineering – COBEM, volume 1, Curitiba.
Pastore, A., Pierella, C., Artoni, F., Pirondini, E., Coscia, M., Casadio, M., and Micera, S. (2018). Motor intention decoding during active and robot-assisted reaching. In 2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob), pages 312–317, Enschede, The Netherlands.
Peña, G. G. (2017). Controle de Impedância Adaptativo Dirigido por EMG para Reabilitação Robótica. phdthesis, Universidade de São Paulo, São Carlos.
Peña, G. G., Consoni, L. J., dos Santos, W. M., and Siqueira, A. A. G. (2019). Feasibility of an optimal emg-driven adaptive impedance control applied to an active knee orthosis. Robotics and Autonomous Systems, (112):98–108.
Ramos-Lima, M., Brasileiro, I., Lima, T., and Braga-Neto, P. (2018). Quality of life after stroke: impact of clinical and sociodemographic factors. Clinics, 73.
Rangel, E. S. S., Belasco, A. G. S., and Diccini, S. (2013). Quality of life of patients with stroke rehabilitation. Acta Paulista de Enfermagem, 26(2):205–212.
SAFANELLI, J., VIEIRA, L. G. D. R., de ARAUJO, T., MANCHOPE, L. F. S., KUHLHOFF, M. H. R., NAGEL, V., CONFORTO, A. B., SILVA, G. S., MAZIN, S., de MAGALHÃES, P. S. C., and CABRAL, N. L. (2019). The cost of stroke in a public hospital in brazil: a one-year prospective study. Arquivos de Neuro-Psiquiatria, 77(6):404–411.
Seth, A., Hicks, J. L., Uchida, T. K., Habib, A., Dembia, C. L., Dunne, J. J., Ong, C. F., DeMers, M. S., Rajagopal, A., Millard, M., Hamner, S. R., Arnold, E. M., Yong, J. R., Lakshmikanth, S. K., Sherman, M. A., Ku, J. P., and Delp, S. L. (2018). OpenSim: Simulating musculoskeletal dynamics and neuromuscular control to study human and animal movement. PLOS Computational Biology, 14(7):e1006223.
Trinler, U., Schwameder, H., Baker, R., and Alexander, N. (2019). Muscle force estimation in clinical gait analysis using AnyBody and OpenSim. Journal of Biomechanics, 86:55–63.
WHO (2011). World health organization - world report on disability.
WHO (2018). World health organization - the top 10 causes of death.
Wolpert, D. M., Miall, R. C., and Kawato, M. (1998). Internal models in the cerebellum. Trends in Cognitive Sciences, 2(9):338–347.
Publicado
14/10/2021
Como Citar
MOSCONI, Denis; SIQUEIRA, Adriano A. G..
Interaction models between humans and lower-limbs exoskeletons applied to robotic neurorehabilitation. In: CONCURSO DE TESES E DISSERTAÇÕES EM ROBÓTICA - CTDR (MESTRADO) - SIMPÓSIO BRASILEIRO DE ROBÓTICA E SIMPÓSIO LATINO-AMERICANO DE ROBÓTICA (SBR/LARS), 9. , 2021, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 34-45.
DOI: https://doi.org/10.5753/wtdr_ctdr.2021.18683.
