The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
A Review on Lower Limb Rehabilitation Exoskeleton Robots
Open accessAbstract
Lower limb rehabilitation exoskeleton robots integrate sensing, control, and other technologies and exhibit the characteristics of bionics, robotics, information and control science, medicine, and other interdisciplinary areas. In this review, the typical products and prototypes of lower limb exoskeleton rehabilitation robots are introduced and state-of-the-art techniques are analyzed and summarized. Because the goal of rehabilitation training is to recover patients’ sporting ability to the normal level, studying the human gait is the foundation of lower limb exoskeleton rehabilitation robot research. Therefore, this review critically evaluates research progress in human gait analysis and systematically summarizes developments in the mechanical design and control of lower limb rehabilitation exoskeleton robots. From the performance of typical prototypes, it can be deduced that these robots can be connected to human limbs as wearable forms; further, it is possible to control robot movement at each joint to simulate normal gait and drive the patient’s limb to realize robot-assisted rehabilitation training. Therefore human–robot integration is one of the most important research directions, and in this context, rigid-flexible-soft hybrid structure design, customized personalized gait generation, and multimodal information fusion are three key technologies.
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Cites
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Cited by
Interactive Control of Lower Limb Exoskeleton Robots: A Review
Zhang, Y.-P., Cao, G.-Z., Li, L.-L., & Diao, D.-F. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2024.3352005 · Cited by 58
Deep Learning Approaches for Enhanced Lower-Limb Exoskeleton Control: A Review
Belal, M., Alsheikh, N., Aljarah, A., & Hussain, I. (2024) · IEEE Access · doi:10.1109/access.2024.3414175 · Cited by 42
Metadata
- Authors
- Shi, D., Zhang, W., Zhang, W., & Ding, X.
- Venue
- Chinese Journal of Mechanical Engineering
- Publisher
- Elsevier BV
- Published
- 2019-08-30
- Volume
- 32
- Issue
- 1
- ISSN
- 1000-9345 (ISSN-L)
- 2192-8258
- OpenAlex
- W2970489687
- Cited by
- 508
- References
- 69
- FWCI
- 14.26
- Type
- journal article
- Language
- en
- Open access
- diamond
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