Effectiveness of robot-assisted gait training on patients with burns: a preliminary study
So Young Joo,
Seung Yeol Lee,
Yoon Soo Cho,
Kuem Ju Lee,
Sang-Hyun Kim and
Cheong Hoon Seo
Computer Methods in Biomechanics and Biomedical Engineering, 2020, vol. 23, issue 12, 888-893
Abstract:
Gait enables individuals to move forward and is considered a natural skill. However, gait disturbances are very common in patients with burn injury. Recent studies have emphasized the role of robot-assisted gait training (RAGT) in rehabilitation. This study aimed to evaluate the efficacy of RAGT on patients with lower extremity burn for the first time. 12 patients with lower extremity burns were included. SUBAR® (CRETEM, Korea) is a wearable robot with a footplate that assists patients to perform voluntary muscle movements. Patients underwent 30 min of RAGT using SUBAR® for 30 min once a day for 5 days a week for 4 weeks. Functional scores of functional ambulation category (FAC), 6-minute walking test (6MWT) distances, and numeric rating scale (NRS) scores of pain before and after 4 weeks RAGT were measured. NRS scores decreased significantly from 6.92 ± 1.78 points before RAGT to 4.17 ± 1.75 points after 4 weeks of RAGT (p = 0.002). FAC scores increased significantly from 1.58 ± 1.08 points to 3.08 ± 1.31 points (p = 0.002). 6MWT scores increased significantly from 182.17 ± 153.62 points to 279.17 ± 119.27 points (p = 0.001). RAGT may facilitate early recovery from a burn injury. This study is the first study to evaluate the effectiveness of RAGT on patients with burns. Outcomes were meaningful, including patient-subjective outcome measures, and objective gait functions for burn patients. The absence of complications on burn patients provides an opportunity to enlarge the application area of RAGT.
Date: 2020
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/10255842.2020.1769080 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:23:y:2020:i:12:p:888-893
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20
DOI: 10.1080/10255842.2020.1769080
Access Statistics for this article
Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton
More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().