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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.
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“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
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Kuswanto, D., Wicaksono, I. A., & Agustin, F. (2018) · doi:10.1109/icstc.2018.8528709 · Cited by 2
A Data-Driven Predictive Model of Individual-Specific Effects of FES on Human Gait Dynamics
Drnach, L., Allen, J. L., Essa, I. A., & Ting, L. H. (2019) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2019.8794304 · Cited by 2
Gait locomotion generation and leg muscle evaluation for overground walking rehabilitation robots
Wang, P. (2012) · doi:10.32657/10356/50714 · Cited by 2
Robotic Assistive Devices for Motor Disability Rehabilitation
Alamdari, A., & Krovi, V. (2016) · Wiley Encyclopedia of Electrical and Electronics Engineering · doi:10.1002/047134608x.w6603.pub2 · Cited by 2
Ajayi, M. O. (2016) · theses.fr (ABES) · doi:10.70675/8118b0bdzca0ez4d48z90cdz3dffb8f1f6ea · Cited by 13
A dynamic model of a device with a parallel-serial structure to support the human lower limb
Ostaszewski, M., & Zdzisław Gosiewski, A. (2018) · Technology and Health Care · doi:10.3233/thc-182505 · Cited by 1
Impedance Synovial Control for Lower Limb Rehabilitation Exoskeleton System
Zhu, X., Sun, Z., & Wang, T. (2022) · Communications in computer and information science · doi:10.1007/978-981-19-7946-0_31 · Cited by 1
Li, H., Sun, C., Zhang, J., & Chen, W. (2022) · IEEE Conference on Industrial Electronics and Applications (ICIEA) · doi:10.1109/iciea54703.2022.10006324 · Cited by 1
Control Design for a Power-Assisted Mobile Trainer: Applied to Clinical Stroke Rehabilitation
Wang, F., Pan, W.-R., Lee, C.-H., Chen, S., Lin, A.-C., Cheng, L.-Y., & Lin, T.-T. (2024) · Machines · doi:10.3390/machines12010061 · Cited by 1
Human-Robot Interaction in Lower Limb Rehabilitation: A Scoping Review
Younis, S., Narayan, J., & Mittal, M. (2024) · Springer eBooks · doi:10.1007/978-981-97-8983-2_11 · Cited by 1
Golyski, P. R., Swaich, N. K., Panizzolo, F. A., & Sawicki, G. S. (2025) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2025.112784 · Cited by 2
Jammot, M., Esser, A., Wolf, P., Riener, R., & Basla, C. (2025) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra55743.2025.11127825 · Cited by 1
Honari, D., Pedrammanesh, A., Peykari, B., Park, E., Arzanpour, S., & Najafi, F. (2025) · IEEE-RAS International Conference on Humanoid Robots (Humanoids) · doi:10.1109/humanoids65713.2025.11203209 · Cited by 1
Yu, S., Fu, R., Ye, C., & Li, H. (2026) · Journal of Mechanisms and Robotics · doi:10.1115/1.4071421 · Cited by 1
Force Control Based on Model Predictive for Lower Limb Rehabilitation Training
Cao, F. C., & Qin, H. W. (2015) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.738-739.991 · Cited by 1
Synthesis of an NR Robot With Four-Bar Constraining Modules
Tsuge, B. Y., & McCarthy, J. M. (2014) · doi:10.1115/detc2014-35371 · Cited by 1
Modelling and control of a leg rehabilitation system for a reconfigurable wheelchair
Fadlallah, S. O., & Goher, K. (2013) · IEEE International Conference on Control System, Computing and Engineering · doi:10.1109/iccsce.2013.6719952 · Cited by 1
Development of a robot-aided neuromuscular rehabilitation method using perturbing forces
Lee, S., & Kim, C. (2013) · IEEE International Symposium on Robotics (ISR) · doi:10.1109/isr.2013.6695681 · Cited by 1
Design of active ankle-foot orthosis based on plantar pressure sensor
Zhang, P., Chen, W., Wang, J., & Zhang, J. (2014) · IEEE Conference on Industrial Electronics and Applications (ICIEA) · doi:10.1109/iciea.2014.6931480 · Cited by 1
Effect of Motor Training for the Upper Extremity using the Haptic Device
Ikeda, Y., Inoue, K., Ito, Y., Terada, T., Takahashi, Y., Nitta, O., Iwasaki, K., & Kaneko, S. (2011) · Rigakuryoho Kagaku · doi:10.1589/rika.26.275 · Cited by 1
Transferring Elementary Characteristics of Human Gait to Mobile Robotic Gait Rehabilitation System
Olenšek, A., Matjačić, Z., Tschakarow, R., Tüttemann, M., & Brendel, T. (2014) · doi:10.2316/p.2014.818-038 · Cited by 1
Design of the control system platform for modular lower extremity rehabilitation exoskeleton
Zhang, W., Qi, C., Shi, D., Sun, L., & Ding, X. (2018) · IEEE Conference on Industrial Electronics and Applications (ICIEA) · doi:10.1109/iciea.2018.8398096 · Cited by 1
Liquid Metal Enabled Flexible Exoskeleton or Artificial Muscle
Liu, J., & Yi, L. (2018) · Springer series in biomaterials science and engineering · doi:10.1007/978-981-10-5607-9_11 · Cited by 1
Elbow training device using the Mechanically Adjustable Stiffness Actuator(MASA)
Choi, J., Son, C., Park, S., Jung, E., & Yu, D. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8512984 · Cited by 1
Design and implementation of a wearable exoskeleton system for lower limbs
Ye, J. (2019) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/612/3/032114 · Cited by 1
Ko, B.-W., & Song, W.-K. (2020) · Journal of Mechanics in Medicine and Biology · doi:10.1142/s0219519420400333 · Cited by 1
Lower limb rehabilitation robot control based on human gait data and plantar reaction force
Ge, Y., Dan, Y., Wang, A., & Zhang, S. (2020) · International Conference on Advanced Mechatronic Systems · doi:10.1109/icamechs49982.2020.9310077 · Cited by 1
Trajectory Tracking Control Based on RTO Enforcing SCFO for Lower Limb Rehabilitation Robot
Chu, Q., Zhang, J., & Chen, Z. (2021) · Chinese Control Conference (CCC) · doi:10.23919/ccc52363.2021.9550218 · Cited by 1
Impedance Control of Upper Limb Rehabilitation Robot Based on Series Elastic Actuator
Gu, J. N., Xu, C., Liu, K., Zhao, L., He, T., & Sun, Z. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-13835-5_13 · Cited by 1
Development of a software-based driving system module for lower limb exoskeleton
Sangeetha, T. S., Sunny, S. M., Sivanandan, K. S., Parameswaran, A. P., & Baiju, T. (2023) · AIP conference proceedings · doi:10.1063/5.0154112 · Cited by 1
Adaptive Radial-Basis Function Neural Network Control of a Pneumatic Actuator
Dinh, V.-V., Pham, B.-L., Nguyen, V.-T., Duong, M. D., & Dao, Q.-T. (2023) · Lecture notes in networks and systems · doi:10.1007/978-981-99-4725-6_32 · Cited by 1
Effect of Lower Limb Exoskeleton Robot on Walking Function of Stroke Patients
Yang, Y., & Lu, J. (2023) · Lecture notes in computer science · doi:10.1007/978-981-99-6489-5_45 · Cited by 1
Test-Stand Experimental Analysis of RoboWalk Weight Assisting Performance
Ghafoori, M., & Moosavian, S. A. A. (2023) · RSI International Conference on Robotics and Mechatronics (ICRoM) · doi:10.1109/icrom60803.2023.10412409 · Cited by 1
Fractional Order Based Controllers For Lower Limb Exoskeleton In Contact Environments
Faraj, M. A., Maalej, B., & Derbel, N. (2023) · International Multi-Conference on Systems, Signals & Devices (SSD) · doi:10.1109/ssd58187.2023.10411254 · Cited by 1
Sato, J. R., Gianlorenço, A. C., Fernandes, E. B., da Rocha, T. F., Makiyama, A. M., & Dipietro, L. (2024) · Journal of Visualized Experiments · doi:10.3791/66004 · Cited by 1
Design and Development of a Lower Limb Rehabilitation Robotic System
Popescu, D., Roibu, H., Manta, L. F., Copilusi, C. P., Geambesa, M., Rusu, L., & Burileanu, A. H. (2024) · International Carpathian Control Conference · doi:10.1109/iccc62069.2024.10569966 · Cited by 1
Transparency Control of a 1-DoF Knee Exoskeleton via Human-in-the-Loop Velocity Optimisation
Cha, L., Guez, A., Chen, C., Kim, S., Yu, Z., Xiao, B. J., & Vaidyanathan, R. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10611632 · Cited by 1
Advances in Robotic Rehabilitation for Lower Limb Recovery and Walking Assistance
González-Mejía, S., & Ramírez, J. M. (2025) · Ingeniería y Competitividad · doi:10.25100/iyc.v27i1.14594 · Cited by 1
Fundamentals of Exoskeleton Robots for Rehabilitation
Cardona, M., & Serrano, F. E. (2025) · Springer eBooks · doi:10.1007/978-3-031-83655-8_1 · Cited by 1
Chances and limits of locomotor trainingafter damage to the central nervous system
Dietz, V. (2012) · Cambridge University Press eBooks · doi:10.1017/cbo9781139030564.027 · Cited by 1
Lab Experiences with a Linkage Exoskeleton for Walking Assistance
Silva, I., Ceccarelli, M., Copilusi, C. P., & Flores, P. (2014) · Mechanisms and machine science · doi:10.1007/978-3-319-09411-3_68 · Cited by 1
Kinematics Characteristic of Exoskeleton Walking Robot for Older People
Chen, Y., Lin, S. Y., Li, R. H., & Zhang, L. D. (2014) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.644-650.167 · Cited by 1
An arm for a leg: Adapting a robotic arm for gait rehabilitation
Franchi, G., Viereck, U., Platt, R., Yen, S., & Hasson, C. J. (2015) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7319253 · Cited by 1
Murray, S. A., & Goldfarb, M. T. (2015) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7318803 · Cited by 1
Synchronization control scheme for gait training robot and treadmill
Karnjanaparichat, T., & Pongvuthithum, R. (2014) · International Computer Science and Engineering Conference · doi:10.1109/icsec.2014.6978244 · Cited by 1
Aliseychik, A. P., Kolesnichenko, E., Glazunov, V. A., Orlov, I. A., Pavlovsky, V. E., & Petrovskaya, N. V. (2016) · Mechanisms and machine science · doi:10.1007/978-3-319-44156-6_45 · Cited by 1
Mir‐Nasiri, N. (2016) · Lecture notes in mechanical engineering · doi:10.1007/978-3-319-33581-0_22 · Cited by 1
Control algorithm and evaluation of a powered wheeled walker for tracking a user
Kim, J.-Y., Park, M.-J., & Park, K. (2017) · Advances in Mechanical Engineering · doi:10.1177/1687814017727250 · Cited by 1
Design and Fabrication of an Active Knee Orthosis for Rehabilitation of Lower Limbs
Rad, M. A. I., Mokhtarian, A., & Karimi, M. T. (2019) · DOAJ (DOAJ: Directory of Open Access Journals) · doi:10.30476/jrsr.2019.75405 · Cited by 1
Xu, J., Xu, L., Liu, J., Chen, S., Xu, C., Liu, Y., & Chen, J. (2019) · International Conference on Advanced Robotics and Mechatronics (ICARM) · doi:10.1109/icarm.2019.8833882 · Cited by 1
Development of a non-actuated wearable device to prevent knee buckling
Naito, S., Akiyama, Y., Ohashi, K., Yamada, Y., & Okamoto, S. (2019) · IEEE Global Conference on Life Sciences and Technologies (LifeTech) · doi:10.1109/lifetech.2019.8884025 · Cited by 1
Research on Lower Limb Exoskeleton Based on Multi-Sensor Information Mature Technology
Li, G., Song, J., Wang, X., Lan, F., & Zou, F. (2019) · IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems · doi:10.1109/cyber46603.2019.9066613 · Cited by 1
Development of a parameter adaptation robot for lower limb rehabilitation
Weida, L., Li, J., Li, X., & Zhang, H. (2019) · IEEE Conference on Cybernetics and Intelligent Systems · doi:10.1109/cis-ram47153.2019.9095792 · Cited by 1
Intended gait speed prediction via swing limb kinematics applicable for patients with slow gait
Kim, J., Kim, Y., Lee, J. M., & Kim, S. (2020) · Electronics Letters · doi:10.1049/el.2020.1245 · Cited by 1
The Design and Development of Sit to Stand Trainer for the Elderly
Saadprai, S., & Rungroungdouyboon, B. (2020) · Walailak Journal of Science and Technology (WJST) · doi:10.48048/wjst.2020.6145 · Cited by 2
Hwang, J., You, S. H., Choi, W. J., & Yi, C. (2021) · Physical Therapy Korea · doi:10.12674/ptk.2021.28.3.215 · Cited by 1
Augmentation and Rehabilitation with Active Orthotic Devices
Onose, G., Morcov, M.-V., Sporea, C., Mirea, A., & Ciobanu, V. (2021) · Contemporary clinical neuroscience · doi:10.1007/978-3-030-54564-2_24 · Cited by 1
Structural Design of Flexible Exoskeketon Based on Walking Environment Analysis
Chen, X., Dong, L., Pan, X., & Huang, R. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-981-19-3927-3_7 · Cited by 1
Luu, T. P. (2014) · doi:10.32657/10356/58912 · Cited by 1
Development of strategies to reduce energy expenditure for lower-limb active orthoses
Sanz‐Merodio, D. (2018) · doi:10.20868/upm.thesis.52593 · Cited by 1
Alotaibi, M. H. (2018) · IUScholarWorks (Indiana University) · doi:10.7912/c2/1402 · Cited by 1
Zhao, G., Alho, E. J. L., Wei, P., Tang, Y., Liu, L., Zhu, L., Yang, Y., Zhang, Y.-Y., Shan, Y., Li, J., et al. (2025) · medRxiv · doi:10.64898/2025.11.28.25340891 · Cited by 2
伸一郎, 前., 愛子, 大., 西尾, 大., 恵健, 平., 木川浩志, & 武田, 英. (2013) · 日本義肢装具学会誌 · doi:10.11267/jspo.29.46
Anwendung von Robotern in der Neurorehabilitation
Dietz, V. (2014) · Springer eBooks · doi:10.1007/978-3-7091-1601-2_9
Design and Control of Robotic Systems for Lower Limb Stroke Rehabilitation
Yurkewich, A. (2015) · Scholarship@Western (Western University)
Model and dynamic analysis in the process of walking
Tong, J., Sheng, S., Chang, W., & Dong, E. (2015) · IEEE International Conference on Mechatronics and Automation (ICMA) · doi:10.1109/icma.2015.7237786
An Active Orthosis for Gait Rehabilitation
Hussain, S., & Xie, S. Q. (2013) · Mechatronics · doi:10.1002/9781118614549.ch6
Customized Robot Aided Gait Training for NeuroRehabilitation
Hussain, S., & Xie, S. Q. (2013) · Biosystems & biorobotics · doi:10.1007/978-3-642-34546-3_37
Exoskeleton Robot Walking on Slope Terrain
Chen, Y., Li, R. H., & Liu, J. W. (2013) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.367.422
Design and Development of Assistive Leg for Lower Limb Rehabilitation
Sribalaji, C. A., Abhishek, S., Harisubramanyabalaji, S. P., & Dash, A. K. (2014) · Advanced materials research · doi:10.4028/www.scientific.net/amr.984-985.1235
Iterative Learning Impedance Control in Gait Rehabilitation Robot
Cao, F. C., Sun, H. X., & Wang, L. R. (2014) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.494-495.1084
Design and Implementation of a Rehabilitation Training Control System for Stroke Patients
Cao, F. C., & Wang, X. (2014) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.670-671.1406
Kumar, N., Haghani, S., & Shetty, D. (2014) · doi:10.1115/imece2014-38028
A MOBILE ARM EXOSKELETON FOR FIREARM AIM STABILIZATION
Baechle, D. M. (2013)
Khoeilar, R. (2025) · Library, Museums and Press - UDSpace (University of Delaware) · doi:10.58088/wzc5-0031
Exercise Programming and Control System of the Leg Rehabilitation Robot RRH1
Kaczmarski, M., & Granosik, G. (2012) · Lecture notes in control and information sciences · doi:10.1007/978-1-4471-2343-9_34
Gait Trajectory Planing for CIE Exoskeleton
Kabaciński, R., Kaczmarek, P., & Kowalski, M. (2015) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-15847-1_13
Development of upper and lower extremity rehabilitation device for brain computer interface
Tharawadeepimuk, K., Kaimuk, P., & Wongsawat, Y. (2012)
Human-Inspired Robotic Exoskeleton for Post-Stroke Gait Rehabilitation
Kora, K., Xie, S. Q., & McDaid, A. (2015) · Advances in computational intelligence and robotics book series · doi:10.4018/978-1-4666-7387-8.ch012
Energy Efficient Autonomous Lower Limb Exoskeleton For Human Motion Enhancement
Mir‐Nasiri, N., & Jo, H. S. (2016) · Swinburne figshare (Swinburne University of Technology) · doi:10.5281/zenodo.1339432
Development of robotic lower-limb prosthetic and orthotic devices
Thapa, S. (2015) · W. S. Hoole Special Collections Library Manuscript Collections
Synthesis of Branch Type Lower Limb Assistive Device
Sun, Y., & Chen, D. (2016) · Lecture notes in electrical engineering · doi:10.1007/978-981-10-2875-5_40
Assistive Optimal Control-on-Request with Application in Standing Balance Therapy and Reinforcement
Mavrommati, A., Ansari, A. R., & Murphey, T. D. (2017) · Springer eBooks · doi:10.1007/978-3-319-40533-9_7
Çelebi, B. (2013) · Sabanci University
Lower Limb Exoskeleton with Hybrid Pneumaticaly Assisted Electric Drive: Models
Orlov, I. A., Aliseychik, A. P., Kolesnichenko, E., Pavlovsky, V. E., Gribkov, D. A., & Podoprosvetov, A. V. (2017) · Mechanisms and machine science · doi:10.1007/978-3-319-61276-8_79
A disturbing recovery approach for lower extremity exoskeletons with passive ankle joints
Wei, W., Cheng, L., Zhang, P., Zhao, S., Li, Q., Xia, Y., Wang, W., & Li, J. (2017) · IEEE International Conference on Mechatronics and Automation (ICMA) · doi:10.1109/icma.2017.8015878
The effects of gait retraining on muscle coordination and functional walking ability post-stroke
Srivastava, S. (2024) · Library, Museums and Press - UDSpace (University of Delaware) · doi:10.58088/pdqt-aa13
Visuelle Bewegungskontrolle geführter Kraftübungen bei jungen Erwachsenen und Senioren
Lösch, C., Nitzsche, N., Maiwald, C. A., Zschäbitz, D., Weigert, M., & Schulz, H. (2018) · German Journal of Exercise and Sport Research · doi:10.1007/s12662-018-0528-x
Individuality-Preserving Gait Pattern Prediction Based on Gait Feature Transitions
Higashiguchi, T., Ukita, N., Kanbara, M., & Hagita, N. (2018) · IEICE Transactions on Information and Systems · doi:10.1587/transinf.2018edp7082
Study on the Fuzzy Control Algorithm for Knee Exoskeleton Based on Co-simulation
Fan, L., Yan, L., & Xiao, J. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-00214-5_137
Electric Stimulation based Weight Discrimination for Paraplegic Wearing Exoskeleton
Li, M., Wang, X., Aoyama, T., & Hasegawa, Y. (2018) · IEEE International Conference on Intelligence and Safety for Robotics (ISR) · doi:10.1109/iisr.2018.8535936
Control Systems for Assistive and Rehabilitation Robotics: A Introduction to the Special Issue
Dixon, W. E. (2018) · IEEE Control Systems · doi:10.1109/mcs.2018.2866602
System identification and HSDBC-optimized PID control of a portable lower-limb rehabilitation device
Fadlallah, S., & Goher, K. (2018) · doi:10.13180/clawar.2018.10-12.09.01
Adaptive Controllers for Assistive Robotic Devices
Koller, J. R. (2017) · Deep Blue (University of Michigan)
Design of a New Lower-Limb Rehabilitation Machine with Independently Controlled Pedals
Zhao, J., She, J., Wang, D., Wu, M., Fukushima, E. F., & Hashimoto, H. (2019) · IEEE International Symposium on Industrial Electronics (ISIE) · doi:10.1109/isie.2019.8781414
Energy transfer for lower limb rehabilitation robot: A Pilot Analysis
Li, J., Chen, D., Li, H., Liu, Q., & Yang, R. (2018) · IEEE International Conference on Information and Automation (ICIA) · doi:10.1109/icinfa.2018.8812449
Hydro-Muscle Actuated Exo-Legs for Therapy and Video Gaming
Ruotolo, S. D., & Benson, N. E. (2016)
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 ›
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