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.
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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]
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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
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