The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Robot Assisted Gait Training With Active Leg Exoskeleton (ALEX)
Abstract
Gait training of stroke survivors is crucial to facilitate neuromuscular plasticity needed for improvements in functional walking ability. Robot assisted gait training (RAGT) was developed for stroke survivors using active leg exoskeleton (ALEX) and a force-field controller, which uses assist-as-needed paradigm for rehabilitation. In this paradigm undesirable gait motion is resisted and assistance is provided towards desired motion. The force-field controller achieves this paradigm by effectively applying forces at the ankle of the subject through actuators on the hip and knee joints. Two stroke survivors participated in a 15-session gait training study each with ALEX. The results show that by the end of the training the gait pattern of the patients improved and became closer to a healthy subject's gait pattern. Improvement is seen as an increase in the size of the patients' gait pattern, increased knee and ankle joint excursions and increase in their walking speeds on the treadmill.
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
“After training with ALEX, the patients' gait pattern are closer to a healthy gait pattern with increased gait size and walking speeds.”
From Recent developments and challenges of lower extremity exoskeletons (2016) · cites this paper as [28]
In the citing paper
“The effectiveness of ALEX has been demonstrated through clinical trials with stroke survivors [28], [29].”
From Recent developments and challenges of lower extremity exoskeletons (2016) · cites this paper as [28]
Citations
Cites
Knowledge of results and motor learning: A review and critical reappraisal.
Salmoni, A. W., Schmidt, R. A., & Walter, C. B. (1984) · Psychological Bulletin · doi:10.1037/0033-2909.95.3.355 · Cited by 1,438
Patient- cooperative strategies for robot-aided treadmill training: first experimental results
Riener, R., Lunenburger, L., Jezernik, S., Anderschitz, M., Colombo, G., & Dietz, V. (2005) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2005.848628 · Cited by 729
Motor learning elicited by voluntary drive
Lotze, M. (2003) · Brain · doi:10.1093/brain/awg079 · Cited by 691
Veneman, J. F., Ekkelenkamp, R., Kruidhof, R., van der Helm, F. C. T., & van der Kooij, H. (2006) · The International Journal of Robotics Research · doi:10.1177/0278364906063829 · Cited by 428
Husemann, B., Müller, F., Krewer, C., Heller, S., & Koenig, E. (2007) · Stroke · doi:10.1161/01.str.0000254607.48765.cb · Cited by 418
Motions or muscles? Some behavioral factors underlying robotic assistance of motor recovery
Hogan, N., Krebs, H. I., Rohrer, B., Palazzolo, J. J., Dipietro, L., Fasoli, S. E., Stein, J. M., Hughs, R., Frontera, W. R., Lynch, D., et al. (2006) · The Journal of Rehabilitation Research and Development · doi:10.1682/jrrd.2005.06.0103 · Cited by 377
Mayr, A., Kofler, M., Quirbach, E., Matzak, H., Fröhlich, K., & Saltuari, L. (2007) · Neurorehabilitation and Neural Repair · doi:10.1177/1545968307300697 · Cited by 371 · cited 1×
“Another gait training study [5] was conducted using Lokomat with 16 stroke patients for nine weeks mostly within three months of onset.”
MethodCai, L. L., Fong, A. J., Otoshi, C. K., Liang, Y., Burdick, J. W., Roy, R. R., & Edgerton, V. R. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.2266-06.2006 · Cited by 345
Active Leg Exoskeleton (ALEX) for Gait Rehabilitation of Motor-Impaired Patients
Banala, S. K., Agrawal, S. K., & Scholz, J. P. (2007) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2007.4428456 · Cited by 320
Gait Pattern in the Early Recovery Period after Stroke*
Quervain, I. A. K., Simon, S. R., Leurgans, S. E., Pease, W. S., & McAllister, D. R. (1996) · Journal of Bone and Joint Surgery · doi:10.2106/00004623-199610000-00008 · Cited by 316
Research works printed but not linked: 2
- 0, Post-stroke rehabilitation fact sheet
- 0, Aha statistics
Cited by
Sorted by citations
Items 301–400 of 751
Functional Design in Rehabilitation: Modular Mechanisms for Ankle Complex
Aggogeri, F., Pellegrini, N., & Adamini, R. (2016) · Applied Bionics and Biomechanics · doi:10.1155/2016/9707801 · Cited by 17
Haarman, J. A. M., Reenalda, J., Buurke, J. H., van der Kooij, H., & Rietman, J. S. (2016) · Journal of Rehabilitation and Assistive Technologies Engineering · doi:10.1177/2055668316676785 · Cited by 18
An Optimal Method of Training the Specific Lower Limb Muscle Group Using an Exoskeletal Robot
Hwang, B., Oh, B., & Jeon, D. (2018) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2018.2816961 · Cited by 17
Classification of error-related potentials evoked during stroke rehabilitation training
Kumar, A., Pirogova, E., Mahmoud, S. S., & Fang, Q. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac1d32 · Cited by 17
Shaping Individualized Impedance Landscapes for Gait Training via Reinforcement Learning
Zhang, Y., Li, S., Nolan, K. J., & Zanotto, D. (2021) · IEEE Transactions on Medical Robotics and Bionics · doi:10.1109/tmrb.2021.3137971 · Cited by 17
Hwang, B., & Jeon, D. (2012) · IEEE/SICE International Symposium on System Integration (SII) · doi:10.1109/sii.2012.6427375 · Cited by 17
Control of the Sit-To-Stand Transfer of a Biped Robotic Device for Postural Rehabilitation
Menga, G., & Ghirardi, M. (2019) · Robotics · doi:10.3390/robotics8040091 · Cited by 17
Exo-Muscle: A Semi-Rigid Assistive Device for the Knee
Zhang, Y., Ajoudani, A., & Tsagarakis, N. G. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3100609 · Cited by 16
A Multistage Hemiplegic Lower-Limb Rehabilitation Robot: Design and Gait Trajectory Planning
Wang, X., Wang, H., Zhang, B., Zheng, D., Yu, H., Cheng, B. H., & Niu, J. (2024) · Sensors · doi:10.3390/s24072310 · Cited by 19
Structural and Kinematic Aspects of a New Ankle Rehabilitation Device
Cazacu, C.-M., & Doroftei, I. (2014) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.658.507 · Cited by 16
Liu, J., Li, X., Marciniak, C. M., Rymer, W. Z., & Zhou, P. (2014) · International Journal of Neural Systems · doi:10.1142/s0129065714500221 · Cited by 15
LOKOIRAN- A novel robot for rehabilitation of spinal cord injury and stroke patients
Taherifar, A., Hadian, M. R., Mousavi, M., Rassaf, A., & Ghiasi, F. (2013) · RSI International Conference on Robotics and Mechatronics (ICRoM) · doi:10.1109/icrom.2013.6510108 · Cited by 16
Views of physiatrists and physical therapists on the use of gait-training robots for stroke patients
Kang, C. G., Chun, M. H., Chang, M. C., Kim, W. D., & Do, K. H. (2016) · Journal of Physical Therapy Science · doi:10.1589/jpts.28.202 · Cited by 16
Lower limb exoskeletons: brief review
Ergasheva, B. I. (2017) · Scientific and technical journal of information technologies mechanics and optics · doi:10.17586/2226-1494-2017-17-6-1153-1158 · Cited by 16
Dao, Q.-T., Nguyen, M. L., & Yamamoto, S.-I. (2019) · Applied Sciences · doi:10.3390/app9122503 · Cited by 16
Control Strategy and Experimental Research of Cable-Driven Lower Limb Rehabilitation Robot
Wang, Y., Wang, K., Li, X., Mo, Z., & Wang, K. C. (2021) · IEEE Access · doi:10.1109/access.2021.3083810 · Cited by 16
Technology of the Robotic Gait Orthosis Lokomat
Riener, R. (2016) · Springer eBooks · doi:10.1007/978-3-319-28603-7_19 · Cited by 16
Brokaw, E. B., Holley, R. J., & Lum, P. S. (2013) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2013.2238251 · Cited by 16
Development of a lower extremity exoskeleton system for human-robot interaction
Kim, S., & Bae, J. (2014) · International Conference on Ubiquitous Robots and Ambient Intelligence · doi:10.1109/urai.2014.7057413 · Cited by 16
Zhang, W., Tomizuka, M., & Bae, J. (2014) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2014.6859402 · Cited by 17
Recent Development and Trends of Clinical-Based Gait Rehabilitation Robots
Low, K. H. (2015) · Springer tracts in advanced robotics · doi:10.1007/978-3-319-12922-8_2 · Cited by 16
Lerner, Z. F., Damiano, D. L., & Bulea, T. C. (2016) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2016.2550860 · Cited by 16
Robotizing Double-Bar Ankle-Foot Orthosis
Noda, T., Takai, A., Teramae, T., Hirookai, E., Hase, K., & Morimoto, J. (2018) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2018.8462911 · Cited by 16
A novel passive pelvic device for assistance during locomotion
Mokhtarian, A., Fattah, A., & Agrawal, S. K. (2010) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2010.5509476 · Cited by 16
Dao, Q.-T., Mai, D.-H., Nguyen, D.-K., & Ly, N.-T. (2022) · Journal of Control Automation and Electrical Systems · doi:10.1007/s40313-022-00902-5 · Cited by 15
A Compatible Design of a Passive Exoskeleton to Reduce the Body–Exoskeleton Interaction Force
Zhou, N., Liu, Y., Song, Q., & Wu, D. (2022) · Machines · doi:10.3390/machines10050371 · Cited by 15
Sarkisian, S. V., Gabert, L., & Lenzi, T. (2023) · Wearable Technologies · doi:10.1017/wtc.2023.20 · Cited by 15
Asymmetric adaptation in human walking using the Tethered Pelvic Assist Device (TPAD)
Vashista, V., Reisman, D. S., & Agrawal, S. K. (2013) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2013.6650385 · Cited by 15
Dynamic research and analyses of a novel exoskeleton walking with humanoid gaits
Pan, D., Gao, F., & Miao, Y. (2013) · Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science · doi:10.1177/0954406213509611 · Cited by 15
Novel actuation design of a gait trainer with shadow leg approach
Meuleman, J., van Asseldonk, E. H. F., & van der Kooij, H. (2013) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2013.6650369 · Cited by 15
Dynamics Modeling and Performance Analysis of RoboWalk
Nabipour, M., & Moosavian, S. A. A. (2018) · RSI International Conference on Robotics and Mechatronics (ICRoM) · doi:10.1109/icrom.2018.8657593 · Cited by 15
A DIY Fabrication Approach of Stretchable Sensors Using Carbon Nano Tube Powder for Wearable Device
Wiranata, A., Ohsugi, Y., Minaminosono, A., Mao, Z., Kurata, H., Hosoya, N., & Maeda, S. (2021) · Frontiers in Robotics and AI · doi:10.3389/frobt.2021.773056 · Cited by 15
He, L., Guo, X.-J., Zhao, C., & Rao, J. (2023) · Biomedicines · doi:10.3390/biomedicines12010041 · Cited by 15
Boosting lower-limb motor imagery performance through an ensemble method for gait rehabilitation
Zhang, J., Liu, D., Chen, W., Pei, Z., & Wang, J. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107910 · Cited by 14
Technology in Rehabilitation: Ethical and Curricular Implications for Physical Therapist Education
Greenfield, B. H., & Musolino, G. M. (2012) · Journal of Physical Therapy Education · doi:10.1097/00001416-201201000-00012 · Cited by 14
Kinematic accuracy reliability research of a novel exoskeleton with series-parallel topology
Pan, D., Gao, F., Huang, X., & Miao, Y. (2013) · Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science · doi:10.1177/0954406213511239 · Cited by 14
Dynamics analysis and simulation verification of a novel knee joint exoskeleton
Fan, L., Yan, L., Xiao, J., & Wang, F. (2017) · Journal of Vibroengineering · doi:10.21595/jve.2017.18323 · Cited by 14
Locomotion Mode Recognition with Inertial Signals for Hip Joint Exoskeleton
Du, G., Zeng, J., Gong, C., & Zheng, E. (2021) · Applied Bionics and Biomechanics · doi:10.1155/2021/6673018 · Cited by 14
Optimal Backstepping Controller Design for Prosthetic Knee Joint
Salman, M. A., & Kadhim, S. K. (2022) · Journal Européen des Systèmes Automatisés · doi:10.18280/jesa.550105 · Cited by 14
Youssofzadeh, V., Zanotto, D., Stegall, P., Naeem, M., Wong‐Lin, K., Agrawal, S. K., & Prasad, G. (2014) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2014.6945083 · Cited by 14
Mechanical Design of a Biomimetic Compliant Lower Limb Exoskeleton (BioComEx)
Başer, Ö., KIZILHAN, H., & Kılıç, E. (2016) · IEEE International Conference on Autonomous Robot Systems and Competitions · doi:10.1109/icarsc.2016.51 · Cited by 14
Brokaw, E. B., Murray, T. M., Nef, T., Lum, P. S., Brokaw, E. B., Nichols, D., & Holley, R. J. (2011) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2011.5975501 · Cited by 13
A novel gait phase-based control strategy for a portable knee-ankle-foot robot
Gong, C., Salim, V., & Yu, H. (2015) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2015.7281261 · Cited by 13
A novel assist-as-needed control method to guide pelvic trajectory for gait rehabilitation
Kang, J., Vashista, V., & Agrawal, S. K. (2015) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2015.7281271 · Cited by 13
Flexible design of a wearable lower limb exoskeleton robot
Chen, C., Zheng, D., Peng, A., Wang, C., & Wu, X. (2013) · IEEE International Conference on Robotics and Biomimetics (ROBIO) · doi:10.1109/robio.2013.6739460 · Cited by 13
Adaptive control of an end-effector based electromechanical gait rehabilitation device
Hussein, S., Schmidt, H., & Krüger, J. (2009) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2009.5209485 · Cited by 13
Human hip joint center analysis for biomechanical design of a hip joint exoskeleton
Yang, W., Yang, C.-J., & Xu, T. (2016) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1500286 · Cited by 13
Marchal–Crespo, L., & Riener, R. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-811995-2.00016-3 · Cited by 13
Mechanical Design and Control Strategy for Hip Joint Power Assisting
Liang, W. (2018) · Journal of Healthcare Engineering · doi:10.1155/2018/9712926 · Cited by 13
Structural design and modal analysis of exoskeleton robot for rehabilitation of lower limb
Yang, K., Jiang, Q. F., Wang, X. L., Chen, Y. W., & Yan, X. (2018) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1087/6/062004 · Cited by 13
Bulea, T. C., Lerner, Z. F., & Damiano, D. L. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8512799 · Cited by 13
Zhong, J. F., Zhu, Y., Zhao, C. S., Han, Z., & Zhang, X. (2020) · Complexity · doi:10.1155/2020/1438391 · Cited by 13
AN REHABILITATION ROBOT DRIVEN BY PNEUMATIC ARTIFICIAL MUSCLES
Zhong, J. F., HE, D., Zhao, C. S., Zhu, Y., & Zhang, Q. (2020) · Journal of Mechanics in Medicine and Biology · doi:10.1142/s0219519420400084 · Cited by 13
Proxy-based impedance control of a cable-driven assistive system
Kong, K. (2012) · Mechatronics · doi:10.1016/j.mechatronics.2012.12.002 · Cited by 13
Development and preliminary testing of a novel wheelchair integrated exercise/ rehabilitation system
Hwang, B., & Jeon, D. (2013) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2013.6650347 · Cited by 13
Huang, G., Chang, S. E., Lai, C.-L., & Chen, C. (2021) · IEEE Access · doi:10.1109/access.2021.3063253 · Cited by 12
Verazaluce-Rodríguez, P. R., Rodríguez-Martínez, P., Neri-Gámez, S., & Hernández-Aquino, R. M. (2013) · Rehabilitación · doi:10.1016/j.rh.2013.04.006 · Cited by 12
Compensation of packet loss for a network-based rehabilitation system
Bae, J., Zhang, W., & Tomizuka, M. (2012) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2012.6224592 · Cited by 12
Endogenous Control of Powered Lower-Limb Exoskeleton
Lee, K., Liu, D., Perroud, L., Chavarriaga, R., & Millán, J. D. R. (2016) · Biosystems & biorobotics · doi:10.1007/978-3-319-46532-6_19 · Cited by 12
An Assistive Control Strategy for Rehabilitation Robots Using Velocity Field and Force Field
Asl, H. J., & Narikiyo, T. (2019) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2019.8779551 · Cited by 12
Rouse, C. A., Cousin, C. A., Allen, B. C., & Dixon, W. E. (2020) · Automatica · doi:10.1016/j.automatica.2020.109294 · Cited by 12
Design, Synthesis, and Experiment of Foot-Driven Lower Limb Rehabilitation Mechanisms
Yu, C., Ye, J., Jia, J., Zhao, X., Chen, Z., & Chen, J. (2021) · Journal of Mechanisms and Robotics · doi:10.1115/1.4051788 · Cited by 12
Study of body weight shifting on robotic assisted gait rehabilitation with NaTUre-gaits
Lim, H. B., Luu, T. P., Hoon, K. H., Qu, X., Tow, A. M., & Low, K. H. (2011) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2011.6094849 · Cited by 12
Aguirre-Ollinger, G., Colgate, J. E., Peshkin, M. A., & Goswami, A. (2011) · PubMed · doi:10.1243/09544119jeim854 · Cited by 12
A model-free control method for estimating the joint angles of the knee exoskeleton
Zhang, Y., Wang, J., Li, W., Yang, P., & Yang, P. (2018) · Advances in Mechanical Engineering · doi:10.1177/1687814018807768 · Cited by 12
NSF DARE—Transforming modeling in neurorehabilitation: Four threads for catalyzing progress
Valero‐Cuevas, F. J., Finley, J. M., Orsborn, A. L., Fung, N., Hicks, J. L., Huang, H., Reinkensmeyer, D. J., Schweighofer, N., Weber, D. J., & Steele, K. M. (2024) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-024-01324-x · Cited by 12
Neural Network Robust Control Based on Computed Torque for Lower Limb Exoskeleton
Han, Y., Ma, H., Wang, Y., Shi, D., Feng, Y., Li, X., Shi, Y., Ding, X., & Zhang, W. (2024) · Chinese Journal of Mechanical Engineering · doi:10.1186/s10033-024-01025-5 · Cited by 11
Shape synthesis of an assistive knee exoskeleton device to support knee joint and rehabilitate gait
Singh, R., Chaudhary, H., & Singh, A. K. (2018) · Disability and Rehabilitation Assistive Technology · doi:10.1080/17483107.2018.1493754 · Cited by 11
An Online Transition of Speed-dependent Reference Joint Trajectories for Robotic Gait Training
Shin, S. Y., & Sulzer, J. S. (2019) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2019.8779359 · Cited by 11
Ren, B. S., Liu, J., & Chen, J. (2020) · International Journal of Advanced Robotic Systems · doi:10.1177/1729881419893493 · Cited by 12
Kumar, A., Fang, Q., & Pirogova, E. (2021) · BioMedical Engineering OnLine · doi:10.1186/s12938-021-00850-2 · Cited by 12
Review of Human-exoskeleton Control Strategy for Lower Limb Rehabilitation Exoskeleton
Long, Y., Guo, H., Chi, Y., & Mo, D. (2023) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2456/1/012002 · Cited by 11
Morganti-Kossmann, C., Raghupathi, R., & Maas, A. I. R. (2012) · Cambridge University Press eBooks · doi:10.1017/cbo9781139030564.019 · Cited by 11
Wade, E., Dye, J., Mead, R., & Matarić, M. J. (2011) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2011.5975358 · Cited by 11
Alamdari, A., & Krovi, V. (2016) · International Journal of Mechanisms and Robotic Systems · doi:10.1504/ijmrs.2016.077035 · Cited by 11
A Novel Elastic Force-Field to Influence Mediolateral Foot Placement During Walking
Nyberg, E. T., Broadway, J., Finetto, C., & Dean, J. C. (2016) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2016.2633960 · Cited by 11
Ma, Q., Ji, L., & Wang, R. (2017) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2017.2774295 · Cited by 12
Martínez, A., Lawson, B. E., & Goldfarb, M. T. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8512807 · Cited by 11
Control of power-augmenting lower extremity exoskeleton while walking with heavy payload
Choi, B., Seo, C., Lee, S., & Kim, B. (2019) · International Journal of Advanced Robotic Systems · doi:10.1177/1729881419830535 · Cited by 11
The Swing Control of Knee Exoskeleton Based on Admittance Model and Nonlinear Oscillator
Han, Y., Zhu, S., Gao, H., Wu, Z., Xu, Y., & Zhou, W. (2019) · Journal of Intelligent & Robotic Systems · doi:10.1007/s10846-019-01133-8 · Cited by 11
An adaptive seamless assist-as-needed control scheme for lower extremity rehabilitation robots
Zhang, X., Yin, G., Li, H., Dong, R., & Hu, H. (2020) · Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering · doi:10.1177/0959651820970720 · Cited by 11
Control of twin-double pendulum lower extremity exoskeleton system with fuzzy logic control method
Tanyıldızı, A. K., Yakut, O., Taşar, B., & Tatar, A. B. (2021) · Neural Computing and Applications · doi:10.1007/s00521-020-05554-7 · Cited by 10
Design and analysis of a gait rehabilitation cable robot with pairwise cable arrangement
Tang, L., & Shi, P. (2021) · Journal of Mechanical Science and Technology · doi:10.1007/s12206-021-0637-6 · Cited by 10
Hybrid Zero Dynamics Control of an Underactuated Lower-Limb Exoskeleton for Gait Guidance
Goo, A. C., Laubscher, C. A., & Sawicki, J. T. (2022) · Journal of Dynamic Systems Measurement and Control · doi:10.1115/1.4053946 · Cited by 10
Exoskeleton Training through Haptic Sensation Transfer in Immersive Virtual Environment
Ye, Y., Shi, Y., Lee, Y.-J., Burks, G., Srinivasan, D., & Du, J. (2022) · ASCE Construction Research Congress (CRC) · doi:10.1061/9780784483961.059 · Cited by 10
A Lower Limb Rehabilitation Robot with Rigid-Flexible Characteristics and Multi-Mode Exercises
Dong, M., Yuan, J., & Li, J. (2022) · Machines · doi:10.3390/machines10100918 · Cited by 10
A new Constant Pushing Force Device for human walking analysis
Lenzo, B., Zanotto, D., Vashista, V., Frisoli, A., & Agrawal, S. K. (2014) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2014.6907769 · Cited by 10
Guo, Z., Ye, J., Zhang, S., Xu, L., Chen, G., Guan, X., Li, Y., & Zhang, Z. (2022) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2021.817446 · Cited by 10
Zhang, W., & Tomizuka, M. (2013) · IFAC Proceedings Volumes · doi:10.3182/20130410-3-cn-2034.00063 · Cited by 10
Ren, S., Wang, W., Hou, Z., Liang, X., Wang, J., & Peng, L. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-04212-7_2 · Cited by 10
Liu, H., Zhu, C. J., Zhou, Z., Dong, Y., Meng, W., & Liu, Q. (2024) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2024.1358022 · Cited by 9
Yang, Z., Jin, H., Gao, W., Wang, E., Shu, Y., Wu, M., & Zhang, S. (2024) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2024.3396369 · Cited by 9
Optimal control-on-request: An application in real-time assistive balance control
Mavrommati, A., Ansari, A. R., & Murphey, T. D. (2015) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2015.7140030 · Cited by 9
Exo skeleton pertinence and control techniques: A state-of-the-art review
Rangan, R. P., & Ramesh Babu, S. (2024) · Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science · doi:10.1177/09544062241226842 · Cited by 9
A New 4M Model-Based Human-Machine Interface for Lower Extremity Exoskeleton Robot
Guo, Z., Fan, Y., Zhang, J., Yu, H., & Yin, Y. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33509-9_55 · Cited by 9
McGrath, R. L., Pires-Fernandes, M., Knarr, B. A., Higginson, J. S., & Sergi, F. (2017) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2017.8009258 · Cited by 10
Lee, L.-W., Li, I.-H., & Liang, T.-W. (2021) · International Journal of Fuzzy Systems · doi:10.1007/s40815-021-01051-8 · Cited by 9
RoboWalk: augmented human-robot mathematical modelling for design optimization
Moosavian, S. A. A., Nabipour, M., Absalan, F., & Akbari, V. (2021) · Mathematical and Computer Modelling of Dynamical Systems · doi:10.1080/13873954.2021.1879874 · Cited by 9
Technology of the Robotic Gait Orthosis Lokomat
Marchal–Crespo, L., & Riener, R. (2022) · Springer eBooks · doi:10.1007/978-3-031-08995-4_29 · Cited by 10
Design Aspects of a New Device for Ankle Rehabilitation
Cazacu, C.-M., & Doroftei, I. (2015) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.809-810.986 · Cited by 9
Metadata
- Authors
- Banala, S. K., Kim, S. H., Agrawal, S. K., & Scholz, J. P.
- Affiliations
- University of Delaware (US)
- ORCID
- Agrawal, Sunil K.
- Venue
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Published
- 2009-02
- Volume
- 17
- Issue
- 1
- Pages
- 2-8
- ISSN
- 1534-4320 (ISSN-L)
- 1558-0210
- OpenAlex
- W2163208146
- Cited by
- 751
- References
- 15
- Citations by year
- 2026: 16 · 2025: 25 · 2024: 35 · 2023: 32 · 2022: 49 · 2021: 53 · 2020: 40 · 2019: 52 · 2018: 64 · 2017: 63 · 2016: 55 · 2015: 52 · 2014: 58 · 2013: 65 · 2012: 35
- FWCI
- 12.61
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Neural Systems and Rehabilitation Engineering (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD 38582, R01HD038582)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Health Sciences › Medicine › Clinical Neurology › Spinal Cord Injury Research
- Keywords
- robot-assisted gait training, stroke rehabilitation, gait pattern, walking speed, treadmill gait
- MeSH terms
- Stroke Rehabilitation, Aged, Algorithms, Ankle, Equipment Design, Gait, Humans, Male, Middle Aged, Robotics, Walking, Treatment Outcome, Gait Disorders, Neurologic, Stroke
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