Musculoskeletal Modeling and Control of the Human Upper Limb during Manual Wheelchair Propulsion: Application in Functional Electrical Stimulation Rehabilitation Therapy

Document Type : Research Paper


Department of Mechanical Engineering, Shiraz University, Shiraz, 71936-16548, Iran


Manual wheelchair users rely on their upper limbs for independence and daily activities. The high incidence of upper limb injuries can be attributed to the significant muscular demands imposed by propulsion as a repetitive movement. People with spinal cord injury are at high risk for upper limb injuries, including neuromusculoskeletal pathologies and nociceptive pain, as human upper limbs are poorly designed to facilitate chronic weight-bearing activities, such as manual wheelchair propulsion. Comprehending the underlying biomechanical mechanisms of motor control and developing appropriate rehabilitation tasks are essential to deal with the effects of poor motor control on the performance of manual wheelchair users and prevent long-term upper limb disability, which can interrupt electrical signals between the brain and muscles. Functional electrical stimulation utilizes low-intensity electrical signals to artificially generate body movements by stimulating the damaged peripheral nerves of patients with impaired motor control. Therefore, this study investigates the central nervous system strategy to control human movements, which can be used for task-specific functional electrical stimulation rehabilitation therapy. To this aim, two degrees of freedom musculoskeletal model of the upper limb, including six muscles, is developed, and an optimal controller consisting of two separate optimal parts is proposed to track the desired trajectories in the joint space and estimate the optimal muscle activations regarding physiological constraints. The simulation results are validated with electromyography datasets collected from twelve participants. This study's primary advantages are generating optimal joint torques, accurate trajectory tracking, and good similarities between estimated and measured muscle activations.


Main Subjects

Publisher’s Note Shahid Chamran University of Ahvaz remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

[1] Gurwitz, J.H., Carlozzi, N.E., Davison, K.K., Evenson, K.R., Gaskin, D.J., Lushniak, B., National Institutes of health pathways to prevention workshop: physical activity and health for wheelchair users, Archives of Rehabilitation Research and Clinical Translation, 3, 2021, 100163.
[2] Curi, H.T., Lima, J.D., Ferretti, E.C., Factors related to propulsion efficiency in manual wheelchair users with paraplegia due to spinal cord injury, Cadernos Brasileiros de Terapia Ocupacional, 28, 2020, 999-1019.
[3] Finley, M.A., Euiler, E., Association of musculoskeletal pain, fear-avoidance factors, and quality of life in active manual wheelchair users with SCI: A pilot study, The Journal of Spinal cord Medicine, 43, 2020, 497-504.
[4] Divanoglou, A., Augutis, M., Sveinsson, T., Hultling, C., Levi, R., Self-reported health problems and prioritized goals in community-dwelling individuals with spinal cord injury in Sweden, Journal of Rehabilitation Medicine, 50, 2018.
[5] Mercer, J.L., Boninger, M., Koontz, A., Ren, D., Dyson-Hudson, T., Cooper, R., Shoulder joint kinetics and pathology in manual wheelchair users, Clinical Biomechanics, 21, 2006, 781-789.
[6] Zamarioli, A., Gene expression and bone loss following spinal cord injury, In Cellular, Molecular, Physiological, and Behavioral Aspects of Spinal Cord Injury, Academic Press, 2022, 81-92.
[7] Vives Alvarado, J.R., Felix, E.R., Gater Jr, D.R., Upper extremity overuse injuries and obesity after spinal cord injury, Topics in Spinal Cord Injury Rehabilitation, 27, 2021, 68-74.
[8] Kesar, T.M., Perumal, R., Reisman, D.S., Jancosko, A., Rudolph, K.S., Higginson, J.S., Binder-Macleod, S.A., Functional electrical stimulation of ankle plantarflexor and dorsiflexor muscles: effects on poststroke gait, Stroke, 40, 2009, 3821-3827.
[9] Khalid, S., Alnajjar, F., Gochoo, M., Renawi, A., Shimoda, S., Robotic assistive and rehabilitation devices leading to motor recovery in upper limb: a systematic review, Disability and Rehabilitation: Assistive Technology, 18, 2023, 658-672.
[10] Yildiz, I., A low-cost and lightweight alternative to rehabilitation robots: omnidirectional interactive mobile robot for arm rehabilitation, Arabian Journal for Science and Engineering, 43, 2018, 1053-1059.
[11] Page, S.J., Levine, P., Leonard, A., Szaflarski, J.P., Kissela, B.M., Modified constraint-induced therapy in chronic stroke: results of a single-blinded randomized controlled trial, Physical Therapy, 88, 2008, 333-340.
[12] Laver, K.E., Lange, B., George, S., Deutsch, J.E., Saposnik, G., Crotty, M., Virtual reality for stroke rehabilitation, Cochrane Database of Systematic Reviews, 11, 2017.
[13] Latreche, A., Kelaiaia, R., Chemori, A., Kerboua, A., A New Home-Based Upper-and Lower-Limb Telerehabilitation Platform with Experimental Validation, Arabian Journal for Science and Engineering, 2023, 1-16.
[14] Latreche, A., Kelaiaia, R., Chemori, A., Kerboua, A., Reliability and validity analysis of MediaPipe-based measurement system for some human rehabilitation motions, Measurement, 214, 2023, 112826.
[15] Marquez-Chin, C., Popovic, M.R., Functional electrical stimulation therapy for restoration of motor function after spinal cord injury and stroke: a review, Biomedical Engineering Online, 19, 2020, 1-25.
[16] Rushton, D.N., Functional electrical stimulation, Physiological Measurement, 18, 1997, 241.
[17] Freeman, C.T., Hughes, A.M., Burridge, J.H., Chappell, P.H., Lewin, P.L., Rogers, E., A model of the upper extremity using FES for stroke rehabilitation, The Journal of Biomechanical Engineering, 131, 2009, 1-12.
[18] Alashram, A.R., Annino, G., Mercuri, N.B., Changes in spasticity following functional electrical stimulation cycling in patients with spinal cord injury: A systematic review, The Journal of Spinal Cord Medicine, 45, 2022, 10-23.
[19] Popovic, D.B., Advances in functional electrical stimulation (FES), Journal of Electromyography and Kinesiology, 24, 2014, 795-802.
[20] Ferrante, S., Chia Bejarano, N., Ambrosini, E., Nardone, A., Turcato, A.M., Monticone, M., Ferrigno, G., Pedrocchi, A., A personalized multi-channel FES controller based on muscle synergies to support gait rehabilitation after stroke, Frontiers in Neuroscience, 10, 2016, 425.
[21] Hodkin, E.F., Lei, Y., Humby, J., Glover, I.S., Choudhury, S., Kumar, H., Perez, M.A., Rodgers, H., Jackson, A., Automated FES for upper limb rehabilitation following stroke and spinal cord injury, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26, 2018, 1067-1074.
[22] Cheung, V.C., Niu, C.M., Li, S., Xie, Q., Lan, N., A novel FES strategy for poststroke rehabilitation based on the natural organization of neuromuscular control, IEEE Reviews in Biomedical Engineering, 12, 2018, 154-167.
[23] Uno, Y., Kawato, M., Suzuki, R., Formation and control of optimal trajectory in human multijoint arm movement, Biological Cybernetics, 61, 1989, 89-101.
[24] Jagodnik, K.M., Van den Bogert, A.J., Optimization and evaluation of a proportional derivative controller for planar arm movement, Journal of Biomechanics, 43, 2010, 1086-1091.
[25] Zadravec, M., Matjačić, Z., Planar arm movement trajectory formation: an optimization based simulation study, Biocybernetics and Biomedical Engineering, 33, 2013, 106-117.
[26] Sharifi, M., Salarieh, H., Behzadipour, S., Nonlinear optimal control of planar musculoskeletal arm model with minimum muscles stress criterion, Journal of Computational and Nonlinear Dynamics, 12, 2017, 011014.
[27] Ghannadi, B., Sharif Razavian, R., McPhee, J., Configuration-dependent optimal impedance control of an upper extremity stroke rehabilitation manipulandum, Frontiers in Robotics and AI, 5, 2018, 124.
[28] Wu, Y., Chen, J., Qiao, H., Anti-interference analysis of bio-inspired musculoskeletal robotic system, Neurocomputing, 436, 2021, 114-125.
[29] Ghorbani, H., Vatankhah, R., Haghpanah, S.A., Zolatash, S., Musculoskeletal Modeling and Simulation of the Human Arm in Rehabilitation by Shoulder Wheel Device Using an Adaptive Robust Control Scheme, Iranian Journal of Science and Technology, Transactions of Mechanical Engineering, 46, 2022, 1067-1078.
[30] Zhao, Y., Zhang, M., Wu, H., He, X., Todoh, M., Neuromechanics-Based Neural Feedback Controller for Planar Arm Reaching Movements, Bioengineering, 10, 2023, 436.
[31] Tahara, K., Kino, H., Reaching movements of a redundant musculoskeletal arm: Acquisition of an adequate internal force by iterative learning and its evaluation through a dynamic damping ellipsoid, Advanced Robotics, 24, 2010, 783-818.
[32] Tahara, K., Kuboyama, Y., Kurazume, R., Iterative learning control for a musculoskeletal arm: Utilizing multiple space variables to improve the robustness, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012, 4620-4625.
[33] Wang, T., Song, A., Adaptive neural fuzzy inference system disturbance observer-based control for reaching movement of musculoskeletal arm model, IEEE Access, 6, 2018, 73030-73040.
[34] Vatankhah, R., Broushaki, M., Alasty, A., Adaptive optimal multi-critic based neuro-fuzzy control of MIMO human musculoskeletal arm model, Neurocomputing, 173, 2016, 1529-1537.
[35] Xiuxiang, C., Ting, W., Yongkun, Z., Wen, Q., Xinghua, Z., An adaptive fuzzy sliding mode control for angle tracking of human musculoskeletal arm model, Computers & Electrical Engineering, 72, 2018, 214-223.
[36] Roelker, S.A., Caruthers, E.J., Baker, R.K., Pelz, N.C., Chaudhari, A.M., Siston, R.A., Interpreting musculoskeletal models and dynamic simulations: causes and effects of differences between models, Annals of Biomedical Eengineering, 45, 2017, 2635-2647.
[37] Kainz, H., Modenese, L., Lloyd, D.G., Maine, S., Walsh, H.P.J., Carty, C.P., Joint kinematic calculation based on clinical direct kinematic versus inverse kinematic gait models, Journal of Biomechanics, 49, 2016, 1658-1669.
[38] Myers, C.A., Laz, P.J., Shelburne, K.B., Davidson, B.S., A probabilistic approach to quantify the impact of uncertainty propagation in musculoskeletal simulations, Annals of Biomedical Engineering, 2015, 43:1098-111.
[39] Anderson, F.C., Pandy, M.G., Dynamic optimization of human walking, The Journal of Biomechanical Engineering, 123, 2001, 381-390.
[40] Thelen, D.G., Anderson, F.C., Using computed muscle control to generate forward dynamic simulations of human walking from experimental data, Journal of Biomechanics, 39, 2006, 1107-1115.
[41] De Groote, F., Demeulenaere, B., Swevers, J., De Schutter, J., Jonkers, I., A physiology-based inverse dynamic analysis of human gait using sequential convex programming: a comparative study, Computer Methods in Biomechanics and Biomedical Engineering, 15, 2012, 1093-1102.
[42] Wesseling, M., De Groote, F., Jonkers, I., The effect of perturbing body segment parameters on calculated joint moments and muscle forces during gait, Journal of Biomechanics, 47, 2014, 596-601.
[43] Wesseling, M., Derikx, L.C., De Groote, F., Bartels, W., Meyer, C., Verdonschot, N., Jonkers, I., Muscle optimization techniques impact the magnitude of calculated hip joint contact forces, Journal of Orthopaedic Research, 33, 2015, 430-438.
[44] Rankin, J.W., Rubenson, J., Hutchinson, J.R., Inferring muscle functional roles of the ostrich pelvic limb during walking and running using computer optimization, Journal of the Royal Society Interface, 13, 2016, 20160035.
[45] Lin, Y.C., Dorn, T.W., Schache, A.G., Pandy, M.G., Comparison of different methods for estimating muscle forces in human movement, Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 226, 2012, 103-112.
[46] Mokhtarzadeh, H., Perraton, L., Fok, L., Muñoz, M.A., Clark, R., Pivonka, P., Bryant, A.L., A comparison of optimisation methods and knee joint degrees of freedom on muscle force predictions during single-leg hop landings, Journal of Biomechanics, 47, 2014, 2863-2868.
[47] Grüne, L., Pannek, J., Nonlinear model predictive control, Springer International Publishing, 2017, 45-69.
[48] Levenberg, K., A method for the solution of certain non-linear problems in least squares, Quarterly of Applied Mathematics, 2, 1944, 164-168.
[49] Altman, A. and Gondzio, J., Regularized symmetric indefinite systems in interior point methods for linear and quadratic optimization, Optimization Methods and Software, 11, 1999, 275-302.
[50] Slowik, J.S., Requejo, P.S., Mulroy, S.J., Neptune, R.R., The influence of wheelchair propulsion hand pattern on upper extremity muscle power and stress, Journal of Biomechanics, 49, 2016, 1554-1561.
[51] Hermens, H.J., Freriks, B., Disselhorst-Klug, C., Rau, G., Development of recommendations for SEMG sensors and sensor placement procedures, Journal of Electromyography and Kinesiology, 10, 2000, 361-374.
[52] Padulo, J., Vando, S., Chamari, K., Chaouachi, A., Bagno, D., Pizzolato, F., Validity of the MarkWiiR for kinematic analysis during walking and running gaits, Biology of Sport, 32, 2015, 53-58.
[53] Ugbolue, U.C., Papi, E., Kaliarntas, K.T., Kerr, A., Earl, L., Pomeroy, V.M., Rowe, P.J., The evaluation of an inexpensive, 2D, video based gait assessment system for clinical use, Gait & Posture, 38, 2013, 483-489.
[54] Halloran, K., Focht, M., Teague, A., Peters, J., Rice, I., Kersh, M., Moving forward: A review of continuous kinetics and kinematics during wheelchair and handcycling propulsion, Journal of Biomechanics, 159, 2023, 111779.
[55] Hajiloo, B., Anbarian, M., Esmaeili, H., Mirzapour, M., The effects of fatigue on synergy of selected lower limb muscles during running, Journal of Biomechanics, 103, 2020, 109692.
[56] Turpin, N.A., Uriac, S., Dalleau, G., How to improve the muscle synergy analysis methodology?, European Journal of Applied Physiology, 121, 2021, 1009-1025.
[57] Cooper, R.A., DiGiovine, C.P., Boninger, M.L., Shimada, S.D., Koontz, A.M., Baldwin, M.A., Filter frequency selection for manual wheelchair biomechanics, Journal of Rehabilitation Research & Development, 39, 2002, 323-336.
[58] Mulroy, S.J., Gronley, J.K., Newsam, C.J., Perry, J., Electromyographic activity of shoulder muscles during wheelchair propulsion by paraplegic persons, Archives of Physical Medicine and Rehabilitation, 77, 1996, 187-193.
[59] Cerquiglini, S., Figura, F., Marchetti, M., Ricci, B., Biomechanics of wheelchair propulsion, In Biomechanics VII-A, Park Press, 1981, 410-419.
[60] Winter, D.A., Biomechanics and motor control of human movement, John Wiley & Sons, 2009.
[61] Holzbaur, K.R., Murray, W.M., Gold, G.E., Delp, S.L., Upper limb muscle volumes in adult subjects, Journal of Biomechanics, 40, 2007, 742-749.
[62] Murray, W.M., Buchanan, T.S., Delp, S.L., The isometric functional capacity of muscles that cross the elbow, Journal of Biomechanics, 33, 2000, 943-952.
[63] Veeger, H.E.J., Yu, B., An, K.N., Rozendal, R.H., Parameters for modeling the upper extremity, Journal of Biomechanics, 30, 1997, 647-652.
[64] Pigeon, P. and Feldman, A.G., Moment arms and lengths of human upper limb muscles as functions of joint angles, Journal of Biomechanics, 29, 1996, 1365-1370.
[65] Tahara, K., Arimoto, S., Sekimoto, M., Luo, Z.W., On control of reaching movements for musculo-skeletal redundant arm model, Applied Bionics and Biomechanics, 6, 2009, 11-26.
[66] Marquardt, D.W., An algorithm for least-squares estimation of nonlinear parameters, Journal of the Society for Industrial and Applied Mathematics, 11, 1963, 431-441.
[67] Chvatal, S.A., Ting, L.H., Voluntary and reactive recruitment of locomotor muscle synergies during perturbed walking, Journal of Neuroscience, 32, 2012, 12237-12250.
[68] Kulig, K., Rao, S.S., Mulroy, S.J., Newsam, C.J., Gronley, J.K., Bontrager, E.L., Perry, J., Shoulder joint kinetics during the push phase of wheelchair propulsion, Clinical Orthopaedics and Related Research, 354, 1998, 132-143.
[69] Gil-Agudo, A., Ama-Espinosa, D., Pérez-Rizo, E., Pérez-Nombela, S., Crespo-Ruiz, B., Shoulder joint kinetics during wheelchair propulsion on a treadmill at two different speeds in spinal cord injury patients, Spinal Cord, 48, 2010, 290-296.
[70] Veeger, H.E.J., Rozendaal, L.A., Van der Helm, F.C.T., Load on the shoulder in low intensity wheelchair propulsion, Clinical Biomechanics, 17, 2002, 211-218.
[71] Collinger, J.L., Boninger, M.L., Koontz, A.M., Price, R., Sisto, S.A., Tolerico, M.L., Cooper, R.A., Shoulder biomechanics during the push phase of wheelchair propulsion: a multisite study of persons with paraplegia, Archives of Physical Medicine and Rehabilitation, 89, 2008, 667-676.
[72] Cooper, R.A., Boninger, M.L., Shimada, S.D, Lawrence, B.M., Glenohumeral joint kinematics and kinetics for three coordinate system representations during wheelchair propulsion1, American Journal of Physical Medicine & Rehabilitation, 78, 1999, 435-446.
[73] Finley, M.A., Rasch, E.K., Keyser, R.E., Rodgers, M.M., The biomechanics of wheelchair propulsion in individuals with and without upper-limb impairment, Journal of Rehabilitation Research & Development, 41, 2004, 385-395.
[74] Robertson, R.N., Boninger, M.L., Cooper, R.A., Shimada, S.D., Pushrim forces and joint kinetics during wheelchair propulsion, Archives of Physical Medicine and Rehabilitation, 77, 1996, 856-864.
[75] Veeger, H.E.J., Van Der Woude, L.H.V., Rozendal, R.H., Load on the upper extremity in manual wheelchair propulsion, Journal of Electromyography and Kinesiology, 1, 1991, 270-280.
[76] Latash M., On primitives in motor control, Motor Control, 24, 2020, 318-46.
[77] Sabick, M.B., Kotajarvi, B.R., An, K.N., A new method to quantify demand on the upper extremity during manual wheelchair propulsion, Archives of Physical Medicine and Rehabilitation, 85, 2004, 1151-1159.
[78] Soltau, S.L., Slowik, J.S., Requejo, P.S., Mulroy, S.J., Neptune, R.R., An investigation of bilateral symmetry during manual wheelchair propulsion, Frontiers in Bioengineering and Biotechnology, 3, 2015, 86.
[79] Lex, C., Maximum tire-road friction coefficient estimation, Verlag der Techn. Univ. Graz, 2015.
[80] Walford, S.L., Rankin, J.W., Mulroy, S.J., Neptune, R.R., The relationship between the hand pattern used during fast wheelchair propulsion and shoulder pain development, Journal of Biomechanics, 116, 2021, 110202.