The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Effects of Training With a Robot-Virtual Reality System Compared With a Robot Alone on the Gait of Individuals After Stroke
Open accessAbstract
Background and Purpose— Training of the lower extremity (LE) using a robot coupled with virtual environments has shown to transfer to improved overground locomotion. The purpose of this study was to determine whether the transfer of training of LE movements to locomotion was greater using a virtual environment coupled with a robot or with the robot alone. Methods— A single, blind, randomized clinical trial was conducted. Eighteen individuals poststroke participated in a 4-week training protocol. One group trained with the robot virtual reality (VR) system and the other group trained with the robot alone. Outcome measures were temporal features of gait measured in a laboratory setting and the community. Results— Greater changes in velocity and distance walked were demonstrated for the group trained with the robotic device coupled with the VR than training with the robot alone. Similarly, significantly greater improvements in the distance walked and number of steps taken in the community were measured for the group that trained with robot coupled with the VR. These differences were maintained at 3 months’ follow-up. Conclusions— The study is the first to demonstrate that LE training of individuals with chronic hemiparesis using a robotic device coupled with VR improved walking ability in the laboratory and the community better than robot training alone.
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Cites
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Treatment-Induced Cortical Reorganization After Stroke in Humans
Liepert, J., Bauder, H., Miltner, W. H. R., Taub, E., & Weiller, C. (2000) · Stroke · doi:10.1161/01.str.31.6.1210 · Cited by 1,404
RELIABILITY OF GAIT PERFORMANCE TESTS IN MEN AND WOMEN WITH HEMIPARESIS AFTER STROKE
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Recovery of walking function in stroke patients: The copenhagen stroke study
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Virtual Environments for Motor Rehabilitation: Review
Holden, M. K. (2005) · CyberPsychology & Behavior · doi:10.1089/cpb.2005.8.187 · Cited by 1,154
Effects of Augmented Exercise Therapy Time After Stroke: A Meta-Analysis
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Cited by
What Is the Evidence for Physical Therapy Poststroke? A Systematic Review and Meta-Analysis
Veerbeek, J. M., van Wegen, E., van Peppen, R., van der Wees, P. J., Hendriks, E., Rietberg, M., & Kwakkel, G. (2014) · PLoS ONE · doi:10.1371/journal.pone.0087987 · Cited by 1,203
Review of control strategies for robotic movement training after neurologic injury
Marchal-Crespo, L., & Reinkensmeyer, D. J. (2009) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-6-20 · Cited by 1,182
Virtual reality for stroke rehabilitation
Laver, K. E., Lange, B., George, S., Deutsch, J. E., Saposnik, G., & Crotty, M. (2017) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd008349.pub4 · Cited by 800
Self-citationSensorimotor training in virtual reality: A review
Adamovich, S. V., Fluet, G. G., Tunik, E., & Merians, A. S. (2009) · NeuroRehabilitation · doi:10.3233/nre-2009-0497 · Cited by 507
Lohse, K. R., Hilderman, C. G. E., Cheung, K. L., Tatla, S., & Van der Loos, H. F. M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0093318 · Cited by 501
Metadata
- Authors
- Mirelman, A., Bonato, P., & Deutsch, J. E.
- Venue
- Stroke
- Published
- 2009-01
- Volume
- 40
- Issue
- 1
- Pages
- 169-174
- ISSN
- 0039-2499 (ISSN-L)
- 1524-4628
- OpenAlex
- W2114282023
- Cited by
- 334
- References
- 31
- FWCI
- 18.95
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Mirelman, A., Bonato, P., & Deutsch, J. E. (2009). Effects of Training With a Robot-Virtual Reality System Compared With a Robot Alone on the Gait of Individuals After Stroke. Stroke. https://doi.org/10.1161/strokeaha.108.516328
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
