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Cited by 154Prosthetics and Rehabilitation RoboticsStroke Rehabilitation and RecoveryRobotic Locomotion and Control

The DOI matches its Crossref record; 146 of the 148 references it cites were found in a registry or an index.

Control strategies for effective robot assisted gait rehabilitation: The state of art and future prospects

Cao, Jinghui, Xie, Sheng Quan, Das, Raj, Zhu, Guo L.·2014·Medical Engineering & Physics
DOI 10.1016/j.medengphy.2014.08.005
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Abstract

A large number of gait rehabilitation robots, together with a variety of control strategies, have been developed and evaluated during the last decade. Initially, control strategies applied to rehabilitation robots were adapted from those applied to traditional industrial robots. However, these strategies cannot optimise effectiveness of gait rehabilitation. As a result, researchers have been investigating control strategies tailored for the needs of rehabilitation. Among these control strategies, assisted-as-needed (AAN) control is one of the most popular research topics in this field. AAN training strategies have gained the theoretical and practical evidence based backup from motor learning principles and clinical studies. Various approaches to AAN training have been proposed and investigated by research groups all around the world. This article presents a review on control algorithms of gait rehabilitation robots to summarise related knowledge and investigate potential trends of development. There are existing review papers on control strategies of rehabilitation robots. The review by Marchal-Crespo and Reinkensmeyer (2009) had a broad cover of control strategies of all kinds of rehabilitation robots. Hussain et al. (2011) had specifically focused on treadmill gait training robots and covered a limited number of control implementations on them. This review article encompasses more detailed information on control strategies for robot assisted gait rehabilitation, but is not limited to treadmill based training. It also investigates the potential to further develop assist-as-needed gait training based on assessments of patients' ability. In this paper, control strategies are generally divided into the trajectory tracking control and AAN control. The review covers these two basic categories, as well as other control algorithm and technologies derived from them, such as biofeedback control. Assessments on human gait ability are also included to investigate how to further develop implementations based on assist-as-needed concept. For the consideration of effectiveness, clinical studies on robotic gait rehabilitation are reviewed and analysed from the viewpoint of control algorithm.

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Crossref · 10.1016/j.medengphy.2014.08.005

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Metadata

Authors
Cao, J., Xie, S. Q., Das, R., & Zhu, G. L.
Affiliations
  • University of Auckland (NZ)
  • Huazhong University of Science and Technology (CN)
Corresponding author
Xie, Sheng Quan
ORCID
Venue
Medical Engineering & Physics
Publisher
IOP Publishing
Published
2014-09-07
Volume
36
Issue
12
Pages
1555-1566
ISSN
  • 1350-4533 (ISSN-L)
  • 1873-4030
DOI
10.1016/j.medengphy.2014.08.005
OpenAlex
W2090854043
Cited by
153
References
148
Citations by year
2026: 7 · 2025: 13 · 2024: 8 · 2023: 17 · 2022: 16 · 2021: 16 · 2020: 12 · 2019: 17 · 2018: 19 · 2017: 13 · 2016: 8 · 2015: 6
FWCI
0.77
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • Medical Engineering & Physics (publishedVersion)
  • PubMed (publishedVersion)
  • RMIT Research Repository (RMIT University Library) (submittedVersion)
  • Figshare (submittedVersion)
Funders
  • University of Auckland Doctoral Scholarship
  • Auckland Medical Research Foundation
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
  • Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
  • Physical Sciences › Engineering › Control and Systems Engineering › Robotic Locomotion and Control
Keywords
assist-as-needed control, trajectory tracking control, biofeedback control, gait analysis, treadmill gait training, motor learning
MeSH terms
Animals, Clinical Trials as Topic, Gait, Humans, Robotics, Gait Disorders, Neurologic

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