The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke
Abstract
Objective To compare the effects of robot-assisted movement training with conventional techniques for the rehabilitation of upper-limb motor function after stroke.Design Randomized controlled trial, 6-month follow-up.Setting A Department of Veterans Affairs rehabilitation research and development center.Participants Consecutive sample of 27 subjects with chronic hemiparesis (>6mo after cerebrovascular accident) randomly allocated to group.Interventions All subjects received twenty-four 1-hour sessions over 2 months. Subjects in the robot group practiced shoulder and elbow movements while assisted by a robot manipulator. Subjects in the control group received neurodevelopmental therapy (targeting proximal upper limb function) and 5 minutes of exposure to the robot in each session.Main outcome measures Fugl-Meyer assessment of motor impairment, FIMtrade mark instrument, and biomechanic measures of strength and reaching kinematics. Clinical evaluations were performed by a therapist blinded to group assignments.Results Compared with the control group, the robot group had larger improvements in the proximal movement portion of the Fugl-Meyer test after 1 month of treatment (P<.05) and also after 2 months of treatment (P<.05). The robot group had larger gains in strength (P<.02) and larger increases in reach extent (P<.01) after 2 months of treatment. At the 6-month follow-up, the groups no longer differed in terms of the Fugl-Meyer test (P>.30); however, the robot group had larger improvements in the FIM (P<.04).Conclusions Compared with conventional treatment, robot-assisted movements had advantages in terms of clinical and biomechanical measures. Further research into the use of robotic manipulation for motor rehabilitation is justified.
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Robot-Assisted Upper and Lower Limb Rehabilitation After Stroke
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Motor control and learning principles for rehabilitation of upper limb movements after brain injury
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Farrell, J. F., Hoffman, H. B., Snyder, J. L., Giuliani, C., & Bohannon, R. W. (2007) · Neurorehabilitation · doi:10.3233/nre-2007-22204 · Cited by 61
“Keywords: Stroke, arm, hand, recovery, rehabilitation”
Controls for the shoulder mechanism of an upper-body exoskeleton for promoting scapulohumeral rhythm
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A Force-Feedback Exoskeleton for Upper-Limb Rehabilitation in Virtual Reality
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The Bobath Concept (NDT) as rehabilitation in stroke patients: A systematic review
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“These treatment techniques are MRP,[18,28] forced use therapy,[19] Robot therapy,[20] POWM,[21] Arm BASIS augmented exercise therapy,[22] gait training,[23] RAS,[26] Constraint‐Induced Movement Therapy,[30] meaningful task-specific training.”
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Control of a Pneumatic Orthosis for Upper Extremity Stroke Rehabilitation
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An Assessment of Robot-Assisted Bimanual Movements on Upper Limb Motor Coordination Following Stroke
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Processing Surface EMG Signals for Exoskeleton Motion Control
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Results of Clinicians Using a Therapeutic Robotic System in an Inpatient Stroke Rehabilitation Unit
Abdullah, H. A., Tarry, C., Lambert, C. L., Barreca, S. R., & Allen, B. (2011) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-8-50 · Cited by 59
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“The popularity of RT for enhancing stroke rehabilitation has increased in the past decade [4, 6, 10–13].”
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Functional Restoration for the Stroke Survivor: Informing the Efforts of Engineers
Patton, J. L., Small, S. L., & Rymer, W. Z. (2008) · Topics in Stroke Rehabilitation · doi:10.1310/tsr1506-521 · Cited by 57
User-Driven Functional Movement Training With a Wearable Hand Robot After Stroke
Park, S., Fraser, M., Weber, L. M., Meeker, C., Bishop, L., Geller, D., Stein, J. M., & Ciocarlie, M. (2020) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2020.3021691 · Cited by 61
“shoulder and elbow); in studies with these devices, Fugl-Meyer (FM) - UL and kinematic parameters show that robotic training produces improved functional gains mostly in the proximal joints [7], [8].”
MethodRobotic therapy for chronic stroke: general recovery of impairment or improved task-specific skill?
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Effects of visual gain on force control at the elbow and ankle
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“Understanding how visual information can be used to improve force control at different joints is important when one considers the increased use of robotic-assisted rehabilitation devices (Shadmehr and Mussa-Ivaldi 1994; Reinkensmeyer et al. 2000; Lum et al. 2002).”
BackgroundWang, C., Phua, K. S., Ang, K. K., Guan, C., Zhang, H., Lin, R., Chua, K. S. G., Ang, B. T., & Kuah, C. W. K. (2009) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner.2009.5109285 · Cited by 56
“Studies in [2],[3] show positive results of robotassisted rehabilitation exercises that helps to promote motor function recovery.”
BackgroundPowell, L., Parker, J., James, M. M., & Mawson, S. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5891 · Cited by 58
Robotics and other devices in the treatment of patients recovering from stroke
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Rehabilitative and assistive wearable mechatronic upper-limb devices: A review
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“This increase in research comes as the earlier devices have been shown to be effective tools for assistance in clinical trials.(6,7) The number of devices entering this research community has generated many reviews.”
MethodThe Home Stroke Rehabilitation and Monitoring System Trial: A Randomized Controlled Trial
Linder, S. M., Rosenfeldt, A. B., Reiss, A., Buchanan, S., Sahu, K., Bay, C. R., Wolf, S. L., & Alberts, J. L. (2012) · International Journal of Stroke · doi:10.1111/j.1747-4949.2012.00971.x · Cited by 54
“In general, robotic devices are thought to facilitate motor recovery by providing guided practice, augmenting the patient’s voluntary efforts, during goal-directed, repetitive movements(13).”
BackgroundAn EMG-based approach for on-line predicted torque control in robotic-assisted rehabilitation
Loconsole, C., Dettori, S., Frisoli, A., Avizzano, C. A., & Bergamasco, M. (2014) · IEEE Haptics Symposium · doi:10.1109/haptics.2014.6775452 · Cited by 55
“Robotic rehabilitation for stroke has been demonstrated to be more effective compared to conventional rehabilitation techniques [4] and to achieve greater improvements in the first months of use [5].”
MethodLearning control in robot-assisted rehabilitation of motor skills – a review
Zhou, S.-H., Fong, J., Crocher, V., Tan, Y., Oetomo, D., & Mareels, I. (2016) · Journal of Control and Decision · doi:10.1080/23307706.2015.1129295 · Cited by 58
Portable and Reconfigurable Wrist Robot Improves Hand Function for Post-Stroke Subjects
Khor, K. X., Chin, P. J. H., Yeong, C. F., Su, E. L. M., Narayanan, A. L. T., Rahman, H. B. A., & Khan, Q. I. (2017) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2017.2692520 · Cited by 55
“FMA [12], [18], [38]–[40].”
Dwivedi, A., Gerez, L. F., Hasan, W., Yang, C.-H., & Liarokapis, M. V. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2925302 · Cited by 55
“In order to accelerate the rehabilitation process of impaired people, it is important to execute repetitive movements and to try to perform daily tasks [3].”
BackgroundVariable Admittance Control of a Hand Exoskeleton for Virtual Reality-Based Rehabilitation Tasks
Topini, A., Sansom, W., Secciani, N., Bartalucci, L., Ridolfi, A., & Allotta, B. (2022) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2021.789743 · Cited by 57
“Robot-based therapy has in fact been proved to be effective and beneficial for both patients, reducing recovery time while increasing results, and therapists, who can exploit real-time monitoring to assess progress and tune the exercises accordingly (Lum et al., 2002; Staubli et al., 2009).”
BackgroundLin, K., Chen, Y.-T., Huang, P.-C., Wu, C., Huang, W.-L., Yang, H.-W., Lai, H.-T., & Lu, H.-J. (2012) · Journal of the Formosan Medical Association · doi:10.1016/j.jfma.2012.08.008 · Cited by 54
Increasing Patient Engagement in Rehabilitation Exercises Using Computer-Based Citizen Science
Laut, J., Cappa, F., Nov, O., & Porfiri, M. (2015) · PLoS ONE · doi:10.1371/journal.pone.0117013 · Cited by 55
“Robotic devices have been identified as an effective means to administer [8–10] or complement these therapeutic treatments [11], and neuroprosthetics [12, 13] may directly enhance motor function.”
MethodA pilot clinical study on robotic assisted rehabilitation in VR with an arm exoskeleton device
Montagner, A., Frisoli, A., Borelli, L., Procopio, C., Bergamasco, M., Carboncini, M. C., & Rossi, B. (2007) · International Conference on Virtual Rehabilitation · doi:10.1109/icvr.2007.4362131 · Cited by 54
“years. Some example include MIT Manus [5 – 7], ARMguide [8, 9], MIME (Mirror Image Movement Enabler) [ 10 ], 1-DoF and 2-DoF devices developed at Saga University [11,12], ARMin [13,14] and Salford Exoskeleton [15].”
BackgroundLong-term Effectiveness of Intensive Therapy in Chronic Stroke
Wu, X., Guarino, P., Lo, A., Peduzzi, P. N., & Wininger, M. (2015) · Neurorehabilitation and neural repair · doi:10.1177/1545968315608448 · Cited by 57
Advanced Myoelectric Control for Robotic Hand-Assisted Training: Outcome from a Stroke Patient
Lu, Z., Tong, R. K., Shin, H., Li, S., & Zhou, P. (2017) · Frontiers in Neurology · doi:10.3389/fneur.2017.00107 · Cited by 54
“Robot-assisted upper limb training is considered to be more efficient (1) and economic (2) than conventional therapy in neurorehabilitation.”
BackgroundFrullo, J. M., Elinger, J., Pehlivan, A. U., Fitle, K., Nedley, K., Francisco, G. E., Sergi, F., & O’Malley, M. K. (2017) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2017.00026 · Cited by 58
“The controller is identical to one developed for upper-limb robotic rehabilitation following chronic stroke (Lum et al., 2002) and later implemented on the MAHI Exo-II rehabilitation robot (Gupta et al., 2008).”
MethodA novel shoulder-elbow exoskeleton with series elastic actuators
Crea, S., Cempini, M., Moisè, M., Baldoni, A., Trigili, E., Marconi, D., Cortese, M. D., Giovacchini, F., Posteraro, F., & Vitiello, N. (2016) · IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) · doi:10.1109/biorob.2016.7523802 · Cited by 53
Driving Motor Recovery After Stroke
Richards, L. G., Hanson, C. S., Wellborn, M., & Sethi, A. (2008) · Topics in Stroke Rehabilitation · doi:10.1310/tsr1505-397 · Cited by 52
Does Shorter Rehabilitation Limit Potential Recovery Poststroke?
Fasoli, S. E., Krebs, H. I., Ferraro, M., Hogan, N., & Volpe, B. T. (2004) · Neurorehabilitation and neural repair · doi:10.1177/0888439004267434 · Cited by 53
EMG Based Control of a Robotic Exoskeleton for Shoulder and Elbow Motion Assist
Rahman, M. H., Ochoa-Luna, C., & Saad, M. (2015) · Journal of Automation and Control Engineering · doi:10.12720/joace.3.4.270-276 · Cited by 53
“Research studies reveal that patients who receive robot-assisted therapy show good improvement of motor skills, when compared to conventional therapy techniques [4]-[6].”
BackgroundA design framework for a home-based stroke rehabilitation system: Identifying the key components
Rennick‐Egglestone, S., Axelrod, L., Nind, T., Turk, R., Wilkinson, A., Burridge, J. H., Fitzpatrick, G., Mawson, S., Robertson, Z., Hughes, A., et al. (2009) · International Conference on Pervasive Computing Technologies for Healthcare · doi:10.4108/icst.pervasivehealth2009.6049 · Cited by 52
“Other studies assess the benefits of collaboration to improve motivation [18, 23].”
BackgroundTurolla, A., Daud, O., Oboe, R., Agostini, M., Tonin, P., Paolucci, S., Sandrini, G., Venneri, A., & Piron, L. (2013) · Computational and Mathematical Methods in Medicine · doi:10.1155/2013/895492 · Cited by 51
“Several haptic robots for rehabilitation were developed and tested, such as the MIT-Manus [13, 14], theMirror ImageMovement Enabler (MIME) [15], theARMGuide [16], and the BiManu-Track [17].”
MethodHsieh, Y., Lin, K., Wu, C., Lien, H., Chen, J., Chen, C.-C., & Chang, W. (2013) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2013.09.018 · Cited by 52
Wolbrecht, E. T., Chan, V., Le, V., Cramer, S. C., Reinkensmeyer, D. J., & Bobrow, J. E. (2007) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/cne.2007.369635 · Cited by 51
Bertomeu-Motos, A., Blanco, A., Badesa, F. J., Barios, J. A., Zollo, L., & García-Aracil, N. (2018) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-018-0348-0 · Cited by 56
Park, J., & Chung, Y. (2018) · Neurorehabilitation · doi:10.3233/nre-172415 · Cited by 51
Parker, J., Powell, L., & Mawson, S. (2019) · Journal of Medical Internet Research · doi:10.2196/15981 · Cited by 51
“At this stage, 72 full papers were obtained and 61 of these were excluded (reasons for exclusion can be found in Multimedia Appendix 2 [74-132]).”
A Cable-Driven Three-DOF Wrist Rehabilitation Exoskeleton With Improved Performance
Shi, K., Song, A., Li, Y., Li, H., Chen, D., & Zhu, L. (2021) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2021.664062 · Cited by 50
“Many related clinical trials based on these robots have been carried out, and the results verified the effectiveness of robot-assisted rehabilitation (Reinkensmeyer et al., 2000; Lum et al., 2002; Kwakkel et al., 2008).”
BackgroundA Real-Time Haptic/Graphic Demonstration of how Error Augmentation can Enhance Learning
Wei, Y., Patton, J. L., Bajaj, P., & Scheidt, R. A. (2006) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2005.1570798 · Cited by 51
A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction
Wöhrle, H., Tabie, M., Kim, S. K., Kirchner, F., & Kirchner, E. A. (2017) · Sensors · doi:10.3390/s17071552 · Cited by 53
“To achieve this, the adaptation of robotic rehabilitation systems (e.g., active orthoses or exoskeletons) [14–22] with real-time analysis of physiological data related to neuronal or muscular activity to predict movements seems to be a promising approach [23–30].”
BackgroundRehabilitation and Health Care Robotics
der Loos, H. F. M. V., & Reinkensmeyer, D. J. (2008) · Springer eBooks · doi:10.1007/978-3-540-30301-5_54 · Cited by 50
Boardsworth, K., Rashid, U., Olsen, S., Ramírez, E. R. R., Browne, W. N., Alder, G., & Signal, N. (2025) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-025-01662-4 · Cited by 62
Verbunt, J., Seelen, H. A. M., Ramos, F. P., Michielsen, B. H., Wetzelaer, W. L. H., & Moennekens, M. (2008) · BMC Neurology · doi:10.1186/1471-2377-8-7 · Cited by 49
“However, recent studies have questioned NDT's additional value in stroke patients [ 28 ,29].”
BackgroundEffective Game use in Neurorehabilitation
Perry, J. C., Andureu, J., Cavallaro, F. I., Veneman, J. F., Carmien, S. P., & Keller, T. (2011) · Advances in game-based learning book series · doi:10.4018/978-1-60960-495-0.ch032 · Cited by 49
Impedance Control for Robotic Rehabilitation: A Robust Markovian Approach
Jutinico, A. L., Jaimes, J. C., Escalante, F. M., Perez-Ibarra, J. C., Terra, M. H., & Siqueira, A. A. G. (2017) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2017.00043 · Cited by 49
“We synthesize a fixed-gain controller using a similar approach presented in Mehling and O’Malley (2014) and dos Santos et al.”
BackgroundMethodEffects of Arm Training with the Robotic Device ARMin I in Chronic Stroke: Three Single Cases
Nef, T., Quinter, G., Müller, R., & Riener, R. (2009) · Neurodegenerative Diseases · doi:10.1159/000262444 · Cited by 49
Brokaw, E. B., Murray, T. M., Nef, T., & Lum, P. S. (2011) · The Journal of Rehabilitation Research and Development · doi:10.1682/jrrd.2010.04.0064 · Cited by 48
“This has motivated a number of robotic strategies to assure proper timing between effort and movement, including movement of the contralateral limb to control movement of the paretic limb in bilateral tasks [32,85–86] and EMG-controlled movement [83,87– 88].”
Fareh, R., Elsabe, A. Y. H., Baziyad, M. S., Kawser, T., Brahmi, B., & Rahman, M. H. (2023) · Sensors · doi:10.3390/s23115054 · Cited by 50
“AR, BT, AA, CPM Shoulder and Elbow [14,15] 2000, 2000 6,6 Have used Admittance and Impedance Control PA, AA, AR Arm [103] 2020 6 Tested with an elderly female participant Wrist [104] 2020 Up to 3 Robot consists of Series elastic actuators with high torque-to-weight ratios”
BackgroundMethodHuman Pose Detection for Robotic-Assisted and Rehabilitation Environments
Hernández, Ó. G., Morell, V., Ramón, J., & Jara, C. A. (2021) · Applied Sciences · doi:10.3390/app11094183 · Cited by 51
“MIME is another well-known upper limb rehabilitation robot, developed for elbow rehabilitation using the master–slave concept [6].”
Method
Metadata
- Authors
- Lum, P. S., Burgar, C. G., Shor, P. C., Majmundar, M., & Van der Loos, M.
- Affiliations
- Virginia Commonwealth University (US)
- ORCID
- Lum, Peter S.
- Venue
- Archives of Physical Medicine and Rehabilitation
- Publisher
- Elsevier BV
- Published
- 2002-07
- Volume
- 83
- Issue
- 7
- Pages
- 952-959
- ISSN
- 0003-9993 (ISSN-L)
- OpenAlex
- W2113585314
- Cited by
- 1,159
- References
- 46
- Citations by year
- 2026: 19 · 2025: 20 · 2024: 25 · 2023: 26 · 2022: 48 · 2021: 34 · 2020: 41 · 2019: 57 · 2018: 67 · 2017: 61 · 2016: 81 · 2015: 58 · 2014: 62 · 2013: 68 · 2012: 55
- FWCI
- 28.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Archives of Physical Medicine and Rehabilitation (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Life Sciences › Neuroscience › Neurology › Transcranial Magnetic Stimulation Studies
- Keywords
- stroke rehabilitation, upper limb motor function, hemiparesis, neurodevelopmental treatment, Fugl-Meyer Assessment, FIM, arm muscle strength, reaching kinematics, chronic stroke
- MeSH terms
- Stroke Rehabilitation, Aged, Analysis of Variance, Arm, Biomechanical Phenomena, Chronic Disease, Feedback, Follow-Up Studies, Humans, Muscle Contraction, Paresis, Robotics, Stress, Mechanical, Motion Therapy, Continuous Passive, Range of Motion, Articular, Treatment Outcome, Sample Size, Stroke
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