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Reviewing Clinical Effectiveness of Active Training Strategies of Platform-Based Ankle Rehabilitation Robots. | LitMetric

Reviewing Clinical Effectiveness of Active Training Strategies of Platform-Based Ankle Rehabilitation Robots.

J Healthc Eng

School of Mechanical Engineering and School of Electronic and Electrical Engineering, University of Leeds, Leeds LS2 9JT, UK.

Published: November 2019

AI Article Synopsis

  • This review evaluates the clinical effectiveness of active training methods used with platform-based ankle rehabilitation robots.
  • It involved a systematic search of English-language studies from 1980 to 2017, resulting in 21 studies with 311 patients, including various training approaches like virtual reality (VR) games and proprioceptive neuromuscular facilitation (PNF).
  • The findings indicate that such training techniques are promising for patient rehabilitation, particularly when combined with VR environments, as they enhance safety, confidence, and treatment outcomes.

Article Abstract

Objective: This review aims to provide a systematical investigation of clinical effectiveness of active training strategies applied in platform-based ankle robots.

Method: English-language studies published from Jan 1980 to Aug 2017 were searched from four databases using key words of "Ankle" AND "Robot" AND "Effect OR Improv OR Increas." Following an initial screening, three rounds of discrimination were successively conducted based on the title, the abstract, and the full paper.

Result: A total of 21 studies were selected with 311 patients involved; of them, 13 studies applied a single group while another eight studies used different groups for comparison to verify the therapeutic effect. Virtual-reality (VR) game training was applied in 19 studies, while two studies used proprioceptive neuromuscular facilitation (PNF) training.

Conclusion: Active training techniques delivered by platform ankle rehabilitation robots have been demonstrated with great potential for clinical applications. Training strategies are mostly combined with one another by considering rehabilitation schemes and motion ability of ankle joints. VR game environment has been commonly used with active ankle training. Bioelectrical signals integrated with VR game training can implement intelligent identification of movement intention and assessment. These further provide the foundation for advanced interactive training strategies that can lead to enhanced training safety and confidence for patients and better treatment efficacy.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5838480PMC
http://dx.doi.org/10.1155/2018/2858294DOI Listing

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