Patient- cooperative strategies for robot-aided treadmill training: first experimental results
Abstract
Task-oriented repetitive movements can improve motor performance in patients with neurological or orthopaedic lesions. The application of robotics and automation technology can serve to assist, enhance, evaluate, and document neurological and orthopedic rehabilitation. This paper deals with the application of "patient-cooperative" techniques to robot-aided gait rehabilitation of neurological disorders. We define patient-cooperative to mean that, during movement, the technical system takes into account the patient's intention and voluntary efforts rather than imposing any predefined movements or inflexible strategies. It is hypothesized that such cooperative robotic approaches can improve the therapeutic outcome compared to classical rehabilitation strategies. New cooperative strategies are presented that detect the patient's voluntary efforts. First, this enables the patient increased freedom of movement by a certain amount of robot compliance. Second, the robot behavior adapts to the existing voluntary motor abilities. And third, the robotic system displays and improves the patient contribution by visual biofeedback. Initial experimental results are presented to evaluate the basic principle and technical function of proposed approaches. Further improvements of the technical design and additional clinical testing is required to prove whether the therapeutic outcome can be enhanced by such cooperative strategies.
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In traditional rehabilitation therapies, intensive labour is involved and physical therapists have to provide highly repetitive training that is usually inefficient.
“In the traditional rehabilitation therapies, intensive labour should be involved, and physical therapists have to provide the patients with highly repetitive training that is usually inefficient [25].”
From Recent developments and challenges of lower extremity exoskeletons (2016) · cites this paper as [25]
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- Authors
- Riener, R., Lunenburger, L., Jezernik, S., Anderschitz, M., Colombo, G., & Dietz, V.
- Affiliations
- ETH Zurich (CH)
- Universitätsklinik Balgrist (CH)
- University of Zurich (CH)
- Venue
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Published
- 2005-09
- Volume
- 13
- Issue
- 3
- Pages
- 380-394
- ISSN
- 1534-4320 (ISSN-L)
- 1558-0210
- OpenAlex
- W2133322641
- Cited by
- 729
- References
- 44
- Citations by year
- 2026: 19 · 2025: 24 · 2024: 26 · 2023: 24 · 2022: 37 · 2021: 38 · 2020: 41 · 2019: 39 · 2018: 42 · 2017: 42 · 2016: 45 · 2015: 44 · 2014: 52 · 2013: 53 · 2012: 39
- FWCI
- 14.75
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Neural Systems and Rehabilitation Engineering (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- treadmill training, robot compliance, adaptive robot behavior, visual biofeedback, neurorehabilitation, motor recovery
- MeSH terms
- Exercise Test, Humans, Leg, Pilot Projects, Robotics, Therapy, Computer-Assisted, User-Computer Interface, Motion Therapy, Continuous Passive, Treatment Outcome, Gait Disorders, Neurologic
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