The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Robotic Orthosis Lokomat: A Rehabilitation and Research Tool
Abstract
The aim of this article is to introduce the robotic orthosis Lokomat, developed to automate treadmill training rehabilitation of locomotion for spinal cord injured and stroke patients, to the Functional Electrical Stimulation (FES) and Neuromodulation research communities, and to report on our newly conducted research. We first illustrate the primary use of Lokomat in rehabilitation and focus on control aspects and algorithms associated with robotic rehabilitation of locomotion. Then we describe two applications where the Lokomat was used as a research tool. The first application is closed-loop control of the FES-induced shank movement and the second is the development of a neural network model of the spinal locomotor centers. This model was used to derive a neural locomotion controller for the Lokomat.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The effectiveness of Lokomat as an intervention in gait rehabilitation to improve overground walking function in neurological patients has been verified through worldwide clinical studies [26].”
From Recent developments and challenges of lower extremity exoskeletons (2016) · cites this paper as [26]
In the citing paper
“In trajectory tracking control, the predefined trajectories of the lower limb joints, usually collected from healthy individuals, are used as the control targets [26].”
From Recent developments and challenges of lower extremity exoskeletons (2016) · cites this paper as [26]
Citations
Cites
Treadmill training of paraplegic patients using a robotic orthosis.
Colombo, G., Joerg, M., Schreier, R., & Dietz, V. (2000) · PubMed · Cited by 1,114
Hesse, S., Bertelt, C., Jahnke, M. T., Schaffrin, A., Baake, P., Maležič, M., & Mauritz, K.-H. (1995) · Stroke · doi:10.1161/01.str.26.6.976 · Cited by 612
Laufband (Treadmill) Therapy in Incomplete Paraplegia and Tetraplegia
Wernig, A., Nanassy, A., & MÜLLER, S. (1999) · Journal of Neurotrauma · doi:10.1089/neu.1999.16.719 · Cited by 160
Transcutaneous Functional Electrical Stimulator “Compex Motion”
Keller, T., Popović, M. R., Pappas, I. P. I., & Müller, P. (2002) · Artificial Organs · doi:10.1046/j.1525-1594.2002.06934.x · Cited by 82
Impedance Control Based Gait-Pattern Adaptation for a Robotic Rehabilitation Device
Jezernik, S., Jezernik, K., & Morari, M. (2002) · IFAC Proceedings Volumes · doi:10.1016/s1474-6670(17)33971-x · Cited by 13
Controlling the human-robot interaction for robotic rehabilitation of locomotion
Jezernik, S., & Morari, M. (2003) · International Workshop on Advanced Motion Control · doi:10.1109/amc.2002.1026904 · Cited by 12
A NOVEL SLIDING MODE CONTROLLER FOR FUNCTIONAL ELECTRICAL STIMULATION
Jezernik, S., Inderbitzin, P., Keller, T., & Riener, R. (2002) · IFAC Proceedings Volumes · doi:10.3182/20020721-6-es-1901.01342 · Cited by 10
Research works printed but not linked: 2
- Jezernik S, Colombo G, Morari M. Joint-angle trajectory adaptation for the robotic orthosis Lokomat. In: Proceedings of the Workshop on European Scientific and Industrial Collaboration (WESIC). Enschede, The Netherlands, 2001: pp 451–456. (available from http://www.aut.ee.ethz.ch)
- Jezernik S, Inderbitzin P, Keller T. Riener R. Sliding mode control of Functional Electrical Stimulation for knee joint angle tracking. Proceedings of the 7th Vienna International Workshop on Functional Electrical Stimulation. Vienna, 2001: pp 160–163.
Cited by
Sorted by citations
Ham, R. V., Sugar, T. G., Vanderborght, B., Hollander, K. W., & Lefeber, D. (2009) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2009.933629 · Cited by 834
Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation
Lebedev, M., & Nicolelis, M. A. L. (2017) · Physiological Reviews · doi:10.1152/physrev.00027.2016 · Cited by 695
Recent developments and challenges of lower extremity exoskeletons
Chen, B., Ma, H., Qin, L.-Y., Gao, F., Chan, K.-M., Law, S.-W., Qin, L., & Liao, W.-H. (2016) · Journal of Orthopaedic Translation · doi:10.1016/j.jot.2015.09.007 · Cited by 501
“The Robotic Orthosis Lokomat was developed by Hocoma (Zurich, Switzerland) for gait rehabilitation; it provides functional walking training for patients with mobility dysfunctions in their lower limbs (Figure 1A) [25,26].”
BackgroundMethodA biologically inspired soft exosuit for walking assistance
Asbeck, A. T., De Rossi, S. M. M., Holt, K. G., & Walsh, C. J. (2015) · The International Journal of Robotics Research · doi:10.1177/0278364914562476 · Cited by 450
Husemann, B., Müller, F., Krewer, C., Heller, S., & Koenig, E. (2007) · Stroke · doi:10.1161/01.str.0000254607.48765.cb · Cited by 418
Review of control strategies for lower-limb exoskeletons to assist gait
Baud, R., Manzoori, A. R., Ijspeert, A. J., & Bouri, M. (2021) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-021-00906-3 · Cited by 394
Stronger, Smarter, Softer: Next-Generation Wearable Robots
Asbeck, A. T., Rossi, S., Galiana, I., Ding, Y., & Walsh, C. J. (2014) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2014.2360283 · Cited by 370
Human–Robot Interaction Control of Rehabilitation Robots With Series Elastic Actuators
Yu, H., Huang, S., Chen, G., Pan, Y., & Guo, Z. (2015) · IEEE Transactions on Robotics · doi:10.1109/tro.2015.2457314 · Cited by 356
Active Exoskeleton Control Systems: State of the Art
Anam, K., & Al-Jumaily, A. A. (2012) · Procedia Engineering · doi:10.1016/j.proeng.2012.07.273 · Cited by 308
Robotic gait rehabilitation and substitution devices in neurological disorders: where are we now?
Calabrò, R. S., Cacciola, A., Bertè, F., Manuli, A., Leo, A., Bramanti, A., Naro, A., Milardi, D., & Bramanti, P. (2016) · Neurological Sciences · doi:10.1007/s10072-016-2474-4 · Cited by 271
Towards more effective robotic gait training for stroke rehabilitation: a review
Pennycott, A., Wyss, D., Vallery, H., Klamroth-Marganska, V., & Riener, R. (2012) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-9-65 · Cited by 265
A light-weight active orthosis for hip movement assistance
Giovacchini, F., Vannetti, F., Fantozzi, M., Cempini, M., Cortese, M., Parri, A., Yan, T., Lefeber, D., & Vitiello, N. (2014) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2014.08.015 · Cited by 257
Grimmer, M., Riener, R., Walsh, C. J., & Seyfarth, A. (2019) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-018-0458-8 · Cited by 249
Aoyagi, D., Ichinose, W. E., Harkema, S. J., Reinkensmeyer, D. J., & Bobrow, J. E. (2007) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2007.903922 · Cited by 249
Effect of timing of hip extension assistance during loaded walking with a soft exosuit
Ding, Y., Panizzolo, F. A., Siviy, C., Malcolm, P., Galiana, I., Holt, K. G., & Walsh, C. J. (2016) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-016-0196-8 · Cited by 250
Biologically-inspired soft exosuit
Asbeck, A. T., Dyer, R. J., Larusson, A. F., & Walsh, C. J. (2013) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2013.6650455 · Cited by 241
Biomechanical and Physiological Evaluation of Multi-Joint Assistance With Soft Exosuits
Ding, Y., Galiana, I., Asbeck, A. T., Rossi, S., Bae, J., Santos, T. R. T., Araújo, V. L., Lee, S., Holt, K. G., & Walsh, C. J. (2016) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2016.2523250 · Cited by 218
Nilsson, A., Vreede, K. S., Häglund, V., Kawamoto, H., Sankai, Y., & Borg, J. (2014) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-11-92 · Cited by 208
Artificial intelligence in physical rehabilitation: A systematic review
Sumner, J., Lim, H. W., Chong, L. S., Bundele, A., Mukhopadhyay, A., & Kayambu, G. (2023) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2023.102693 · Cited by 230
Hobbs, B., & Artemiadis, P. (2020) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2020.00019 · Cited by 182
Näf, M. B., Junius, K., Rossini, M., Rodriguez‐Guerrero, C., Vanderborght, B., & Lefeber, D. (2018) · Applied Mechanics Reviews · doi:10.1115/1.4042523 · Cited by 159
Self-Alignment Mechanisms for Assistive Wearable Robots: A Kinetostatic Compatibility Method
Cempini, M., Rossi, S., Lenzi, T., Vitiello, N., & Carrozza, M. C. (2012) · IEEE Transactions on Robotics · doi:10.1109/tro.2012.2226381 · Cited by 157
Arm rehabilitation with a robotic exoskeleleton in Virtual Reality
Frisoli, A., Borelli, L., Montagner, A., Marcheschi, S., Procopio, C., Salsedo, F., Bergamasco, M., Carboncini, M. C., Tolaini, M., & Rossi, B. (2007) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2007.4428491 · Cited by 156
Lower limb rehabilitation exoskeleton robot: A review
Zhou, J., Yang, S., & Xue, Q. (2021) · Advances in Mechanical Engineering · doi:10.1177/16878140211011862 · Cited by 136
Design of two lightweight, high-bandwidth torque-controlled ankle exoskeletons
Witte, K. A., Zhang, J., Jackson, R. W., & Collins, S. H. (2015) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2015.7139347 · Cited by 133
Harib, O., Hereid, A., Agrawal, A., Gurriet, T., Finet, S., Boéris, G., Duburcq, A., Mungai, M. E., Masselin, M., Ames, A. D., et al. (2018) · IEEE Control Systems · doi:10.1109/mcs.2018.2866604 · Cited by 131
A hip–knee–ankle exoskeleton emulator for studying gait assistance
Bryan, G. M., Franks, P. W., Klein, S. C., Peuchen, R. J., & Collins, S. H. (2020) · The International Journal of Robotics Research · doi:10.1177/0278364920961452 · Cited by 126
Control design of a novel compliant actuator for rehabilitation robots
Yu, H., Sunan, H., Gong, C., & Thakor, N. V. (2013) · Mechatronics · doi:10.1016/j.mechatronics.2013.08.004 · Cited by 126
Perspectives and Challenges in Robotic Neurorehabilitation
Iandolo, R., Marini, F., Semprini, M., Laffranchi, M., Mugnosso, M., Cherif, A., Michieli, L. D., Chiappalone, M., & Zenzeri, J. (2019) · Applied Sciences · doi:10.3390/app9153183 · Cited by 131
Durandau, G., Farina, D., Asín-Prieto, G., Dimbwadyo-Terrer, I., Lara, S. L., Pons, J. L., Moreno, J. C., & Sartori, M. (2019) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-019-0559-z · Cited by 122
Sensing Pressure Distribution on a Lower-Limb Exoskeleton Physical Human-Machine Interface
Rossi, S., Vitiello, N., Lenzi, T., Ronsse, R., Koopman, B., Persichetti, A., Vecchi, F., Ijspeert, A. J., van der Kooij, H., & Carrozza, M. C. (2010) · Sensors · doi:10.3390/s110100207 · Cited by 120
Robotic training and spinal cord plasticity
Edgerton, V. R., & Roy, R. R. (2008) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2008.09.018 · Cited by 112
Interactive visuo-motor therapy system for stroke rehabilitation
Eng, K., Siekierka, E., Pyk, P., Chevrier, E., Hauser, Y., Cameirão, M. S., Holper, L., Hägni, K., Zimmerli, L., Duff, A., et al. (2007) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-007-0239-1 · Cited by 111
Brain Computer Interfaces in Rehabilitation Medicine
Bockbrader, M. A., Francisco, G. E., Lee, R., Olson, J. D., Solinsky, R. J., & Boninger, M. L. (2018) · PM&R · doi:10.1016/j.pmrj.2018.05.028 · Cited by 116
Kim, S., & Bae, J. (2017) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2017.2687979 · Cited by 106
Adaptive robotic rehabilitation of locomotion: a clinical study in spinally injured individuals
Jezernik, S., Schärer, R., Colombo, G., & Morari, M. (2003) · Spinal Cord · doi:10.1038/sj.sc.3101518 · Cited by 105
A soft exosuit for patients with stroke: Feasibility study with a mobile off-board actuation unit
Bae, J., Rossi, S., O’Donnell, K., Hendron, K. L., Awad, L. N., Santos, T. R. T., Araújo, V. L., Ding, Y., Holt, K. G., Ellis, T. D., et al. (2015) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2015.7281188 · Cited by 104
Advanced technology for gait rehabilitation: An overview
Mikołajczyk, T., Ciobanu, I., Badea, D. I., Iliescu, A. N., Pizzamiglio, S., Schauer, T., Seel, T., Seiciu, P. L., Turner, D. L., & Berteanu, M. (2018) · Advances in Mechanical Engineering · doi:10.1177/1687814018783627 · Cited by 106
Human-in-the-Loop Optimization of Exoskeleton Assistance Via Online Simulation of Metabolic Cost
Gordon, D., McGreavy, C., Christou, A., & Vijayakumar, S. (2022) · IEEE Transactions on Robotics · doi:10.1109/tro.2021.3133137 · Cited by 102
Pesenti, M., Antonietti, A., Gandolla, M., & Pedrocchi, A. (2021) · Sensors · doi:10.3390/s21030808 · Cited by 97
Baronchelli, F., Zucchella, C., Serrao, M., Intiso, D., & Bartolo, M. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.661815 · Cited by 103
Robot-assisted gait rehabilitation: From exoskeletons to gait systems
Low, K. H. (2011) · Defense Science Research Conference and Expo (DSR) · doi:10.1109/dsr.2011.6026886 · Cited by 95
Design and Control of a Lower Limb Exoskeleton for Robot-Assisted Gait Training
Beyl, P., Damme, M. V., Ham, R. V., Vanderborght, B., & Lefeber, D. (2009) · Applied Bionics and Biomechanics · doi:10.1080/11762320902784393 · Cited by 93
A Flexible Sensor Technology for the Distributed Measurement of Interaction Pressure
Donati, M., Vitiello, N., Rossi, S., Lenzi, T., Crea, S., Persichetti, A., Giovacchini, F., Koopman, B., Podobnik, J., Munih, M., et al. (2013) · Sensors · doi:10.3390/s130101021 · Cited by 88
Robotic Automated External Defibrillator Ambulance for Emergency Medical Service in Smart Cities
Samani, H. A., & Zhu, R. (2016) · IEEE Access · doi:10.1109/access.2016.2514263 · Cited by 87
Design of Smart Modular Variable Stiffness Actuators for Robotic-Assistive Devices
Grosu, V., Rodriguez‐Guerrero, C., Grosu, S., Vanderborght, B., & Lefeber, D. (2017) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2017.2704665 · Cited by 87
Selfslagh, A., Shokur, S., Campos, D. S. F., Donati, A. R. C., Almeida, S., Yamauti, S. Y., Coelho, D. B., Bouri, M., & Nicolelis, M. A. L. (2019) · Scientific Reports · doi:10.1038/s41598-019-43041-9 · Cited by 78
Krewer, C., Müller, F., Husemann, B., Heller, S., Quintern, J., & Koenig, E. (2006) · Gait & Posture · doi:10.1016/j.gaitpost.2006.10.003 · Cited by 80
Influence of body weight unloading on human gait characteristics: a systematic review
Apte, S., Plooij, M., & Vallery, H. (2018) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-018-0380-0 · Cited by 79
dos Santos, M. B., de Oliveira, C. B., dos Santos, A., Pires, C. V. G., Dylewski, V., & Arida, R. M. (2018) · Behavioural Neurology · doi:10.1155/2018/2892065 · Cited by 79
Spinal Cord Injury Rehabilitation
Sipski, M. L., & Richards, J. S. (2006) · American Journal of Physical Medicine & Rehabilitation · doi:10.1097/01.phm.0000202105.87011.bf · Cited by 75
Applications of Brain–Machine Interface Systems in Stroke Recovery and Rehabilitation
Venkatakrishnan, A., Francisco, G. E., & Contreras-Vidal, J. L. (2014) · Current Physical Medicine and Rehabilitation Reports · doi:10.1007/s40141-014-0051-4 · Cited by 75
Measuring human–robot interaction on wearable robots: A distributed approach
Lenzi, T., Vitiello, N., Rossi, S., Persichetti, A., Giovacchini, F., Roccella, S., Vecchi, F., & Carrozza, M. C. (2011) · Mechatronics · doi:10.1016/j.mechatronics.2011.04.003 · Cited by 74
A low cost real-time motion tracking approach using webcam technology
Krishnan, C., Washabaugh, E. P., & Seetharaman, Y. (2014) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2014.11.048 · Cited by 68
Pneumatic Quasi-Passive Actuation for Soft Assistive Lower Limbs Exoskeleton
Natali, C. D., Sadeghi, A., Mondini, A., Bottenberg, E., Hartigan, B., de Eyto, A., O'Sullivan, L. W., Rocón, E., Stadler, K. S., Mazzolai, B., et al. (2020) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2020.00031 · Cited by 67
MINDWALKER: Going one step further with assistive lower limbs exoskeleton for SCI condition subjects
Gancet, J., Ilzkovitz, M., Motard, E., Nevatia, Y., Letier, P., Weerdt, D. D., Cheron, G. A., Hoellinger, T., Seetharaman, K., Petieau, M., et al. (2012) · IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) · doi:10.1109/biorob.2012.6290688 · Cited by 69
Conner, B. C., Luque, J., & Lerner, Z. F. (2020) · Annals of Biomedical Engineering · doi:10.1007/s10439-020-02454-8 · Cited by 65
Han, H., Wang, W., Zhang, F., Li, X., Chen, J., Han, J., & Zhang, J. (2021) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2021.3082198 · Cited by 63
Design and control of the lower limb exoskeleton KIT-EXO-1
Beil, J., Perner, G., & Asfour, T. (2015) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2015.7281186 · Cited by 63
Effects of a powered ankle-foot orthosis on perturbed standing balance
Emmens, A. R., van Asseldonk, E. H. F., & van der Kooij, H. (2018) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-018-0393-8 · Cited by 62
A survey on soft lower limb cable-driven wearable robots without rigid links and joints
Mahmoudi, A., & Najafi, F. (2021) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2021.103846 · Cited by 60
Rossi, S., Colazza, A., Petrarca, M., Castelli, E., Cappa, P., & Krebs, H. I. (2013) · PLoS ONE · doi:10.1371/journal.pone.0073139 · Cited by 60
Tan, C. K., Kadone, H., Watanabe, H., Marushima, A., Yamazaki, M., Sankai, Y., & Suzuki, K. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00276 · Cited by 60
Neuromusculoskeletal Modeling-Based Prostheses for Recovery After Spinal Cord Injury
Pizzolato, C., Saxby, D. J., Palipana, D. B., Diamond, L. E., Barrett, R., Teng, Y. D., & Lloyd, D. G. (2019) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2019.00097 · Cited by 60
Systematic Design of a Parallel Robotic System for Lower Limb Rehabilitation
Vaida, C. L., Bîrlescu, I., Pîslă, A., Ulinici, I., Tarniţă, D., Carbone, G., & Pisla, D. L. (2020) · IEEE Access · doi:10.1109/access.2020.2974295 · Cited by 60
Development of a human neuro-musculo-skeletal model for investigation of spinal cord injury
Paul, C., Bellotti, M., Jezernik, S., & Curt, A. E. P. (2005) · Biological Cybernetics · doi:10.1007/s00422-005-0559-x · Cited by 59
A versatile wire robot concept as a haptic interface for sport simulation
Zitzewitz, J. V., Rauter, G., Steiner, R., Brunschweiler, A., & Riener, R. (2009) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2009.5152219 · Cited by 59
Design and Analysis of a Cable-Driven Articulated Rehabilitation System for Gait Training
Alamdari, A., & Krovi, V. (2015) · Journal of Mechanisms and Robotics · doi:10.1115/1.4032274 · Cited by 59
Narayan, J., & Dwivedy, S. K. (2021) · Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine · doi:10.1177/0954411921994940 · Cited by 56
An Assistive Robotic Device That Can Synchronize to the Pelvic Motion During Human Gait Training
Aoyagi, D., Ichinose, W. E., Harkema, S. J., Reinkensmeyer, D. J., & Bobrow, J. E. (2005) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2005.1502026 · Cited by 56
Gait Trajectory and Event Prediction from State Estimation for Exoskeletons During Gait
Tanghe, K., Groote, F. D., Lefeber, D., Schutter, J. D., & Aertbeliën, E. (2019) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2019.2950309 · Cited by 55
An exoskeleton for gait rehabilitation: Prototype design and control principle
Beyl, P., Damme, M. V., Ham, R. V., Versluys, R., Vanderborght, B., & Lefeber, D. (2008) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2008.4543506 · Cited by 54
A review in gait rehabilitation devices and applied control techniques
Chaparro-Cárdenas, S. L., Lozano-Guzmán, A., Ramirez-Bautista, J. A., & Zavala, A. H. (2018) · Disability and Rehabilitation Assistive Technology · doi:10.1080/17483107.2018.1447611 · Cited by 54
RISE-based adaptive control for EICoSI exoskeleton to assist knee joint mobility
Sherwani, K. I. K., Kumar, N., Chemori, A., Khan, M., & Mohammed, S. (2019) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2019.103354 · Cited by 54
Robotic neurorehabilitation in patients with chronic stroke
Calabrò, R. S., Cola, M. C. D., Leo, A., Reitano, S., Balletta, T., Trombetta, G., Naro, A., Russo, M., Bertè, F., Luca, R. D., et al. (2015) · International Journal of Rehabilitation Research · doi:10.1097/mrr.0000000000000114 · Cited by 51
Delisle-Rodríguez, D., Cardoso, V. F., Gurve, D., Loterio, F. A., Romero-Laiseca, M. A., Krishnan, S., & Bastos-Filho, T. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab08c8 · Cited by 49
Conner, B. C., Remec, N. M., Orum, E. K., Frank, E. M., & Lerner, Z. F. (2020) · IEEE Open Journal of Engineering in Medicine and Biology · doi:10.1109/ojemb.2020.3035316 · Cited by 50
Design and numerical characterization of a new leg exoskeleton for motion assistance
Copilusi, C. P., Ceccarelli, M., & Carbone, G. (2014) · Robotica · doi:10.1017/s0263574714002069 · Cited by 45
Robotic assisted rehabilitation in Virtual Reality with the L-EXOS
Antonio, F., Bergamasco, M., Carboncini, M. C., & Bruno, R. (2009) · Studies in health technology and informatics · doi:10.3233/978-1-60750-018-6-40 · Cited by 44
Torrealba, R. R., Udelman, S. B., & Fonseca-Rojas, E. D. (2017) · Mechanism and Machine Theory · doi:10.1016/j.mechmachtheory.2017.05.024 · Cited by 44
Conner, B. C., Remec, N. M., & Lerner, Z. F. (2022) · Clinical Rehabilitation · doi:10.1177/02692155221087084 · Cited by 43
Rahman, S. M. M., & Ikeura, R. (2012) · Procedia Engineering · doi:10.1016/j.proeng.2012.07.207 · Cited by 43
Mokhtari, M., Taghizadeh, M., & Mazare, M. (2021) · Meccanica · doi:10.1007/s11012-021-01308-4 · Cited by 43
Hasan, S., & Dhingra, A. K. (2022) · Results in Control and Optimization · doi:10.1016/j.rico.2022.100107 · Cited by 43
Human-robot interaction tests on a novel robot for gait assistance
Tagliamonte, N. L., Sergi, F., Carpino, G., Accoto, D., & Guglielmelli, E. (2013) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2013.6650387 · Cited by 42
Stiffness Perception During Active Ankle and Knee Movement
Azocar, A. F., & Rouse, E. J. (2017) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2017.2691308 · Cited by 41
Guo, C., & Li, H. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.948303 · Cited by 43
A novel compact compliant actuator design for rehabilitation robots
Yu, H., Huang, S., Thakor, N. V., Chen, G., Toh, S. L., Cruz, M. S., Ghorbel, Y., & Zhu, C. (2013) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2013.6650478 · Cited by 41
A gait rehabilitation strategy inspired by an iterative learning algorithm
Bae, J., & Tomizuka, M. (2012) · Mechatronics · doi:10.1016/j.mechatronics.2012.01.009 · Cited by 40
Zhang, J., Cheah, C. C., & Collins, S. H. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-803766-9.00007-5 · Cited by 40
Fatai, S., Yap, H. J., Ghazilla, R. A. R., & Ahmad, N. (2018) · PLoS ONE · doi:10.1371/journal.pone.0200193 · Cited by 40
The MACCEPA actuation system as torque actuator in the gait rehabilitation robot ALTACRO
Cherelle, P., Grosu, V., Beyl, P., Mathys, A., Ham, R. V., Damme, M. V., Vanderborght, B., & Lefeber, D. (2010) · IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) · doi:10.1109/biorob.2010.5627030 · Cited by 40
Synthesis of a Pattern Generation Mechanism for Gait Rehabilitation
Ji, Z., & Manna, Y. A. (2008) · Journal of Medical Devices · doi:10.1115/1.2975964 · Cited by 40
Effects of added inertia and body weight support on lateral balance control during walking
Pennycott, A., Wyss, D., Vallery, H., & Riener, R. (2011) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2011.5975415 · Cited by 40
LOPES: a lower extremity powered exoskeleton
Ekkelenkamp, R., Veneman, J. F., & van der Kooij, H. (2007) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2007.363952 · Cited by 40
Kim, J., Gu, G. M., & Heo, P. (2015) · Biosystems & biorobotics · doi:10.1007/978-3-319-21813-7_21 · Cited by 39
Hybrid Adaptive Robust Control Based on CPG and ZMP for a Lower Limb Exoskeleton
Mokhtari, M., Taghizadeh, M., & Mazare, M. (2020) · Robotica · doi:10.1017/s0263574720000260 · Cited by 39
Rehabilitation robotics after stroke: a bibliometric literature review
Zuccon, G., Lenzo, B., Bottin, M., & Rosati, G. (2022) · Expert Review of Medical Devices · doi:10.1080/17434440.2022.2096438 · Cited by 39
A review on the application of autonomous and intelligent robotic devices in medical rehabilitation
García, A., Fuentes-Aguilar, R. Q., Salgado, I., & Chaírez, I. (2022) · Journal of the Brazilian Society of Mechanical Sciences and Engineering · doi:10.1007/s40430-022-03692-8 · Cited by 41
EXiO—A Brain-Controlled Lower Limb Exoskeleton for Rhesus Macaques
Vouga, T., Zhuang, K., Olivier, J., Lebedev, M., Nicolelis, M. A. L., Bouri, M., & Bleuler, H. (2017) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2017.2659654 · Cited by 40
Metadata
- Authors
- Jezernik, S., Colombo, G., Keller, T., Frueh, H., & Morari, M.
- Affiliations
- University of Zurich (CH)
- Universitätsklinik Balgrist (CH)
- ETH Zurich (CH)
- Corresponding author
- Jezernik, Sašo
- Venue
- Neuromodulation Technology at the Neural Interface
- Publisher
- Elsevier BV
- Published
- 2003-04
- Volume
- 6
- Issue
- 2
- Pages
- 108-115
- ISSN
- 1094-7159 (ISSN-L)
- OpenAlex
- W2105236479
- Cited by
- 503
- References
- 7
- Citations by year
- 2026: 9 · 2025: 14 · 2024: 21 · 2023: 40 · 2022: 28 · 2021: 46 · 2020: 35 · 2019: 45 · 2018: 32 · 2017: 32 · 2016: 25 · 2015: 29 · 2014: 26 · 2013: 29 · 2012: 14
- FWCI
- 2.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neuromodulation Technology at the Neural Interface (publishedVersion)
- PubMed (publishedVersion)
- TECNALIA Publications (Fundación TECNALIA Research & Innovation) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Health Sciences › Medicine › Clinical Neurology › Spinal Cord Injury Research
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Keywords
- Lokomat, robotic orthosis, gait rehabilitation, treadmill training, spinal cord injury, stroke, functional electrical stimulation, feedback control
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review