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"Soojeong Kim"

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"Soojeong Kim"

Original Article
Improved Gait Speed After Robot-Assisted Gait Training in Patients With Motor Incomplete Spinal Cord Injury: A Preliminary Study
Seungwon Hwang, Hye-Ri Kim, Zee-A Han, Bum-Suk Lee, Soojeong Kim, Hyunsoo Shin, Jae-Gun Moon, Sung-Phil Yang, Mun-Hee Lim, Duk-Youn Cho, Hayeon Kim, Hye-Jin Lee
Ann Rehabil Med 2017;41(1):34-41.   Published online February 28, 2017
DOI: https://doi.org/10.5535/arm.2017.41.1.34
Objective

To evaluate the clinical features that could serve as predictive factors for improvement in gait speed after robotic treatment.

Methods

A total of 29 patients with motor incomplete spinal cord injury received 4-week robot-assisted gait training (RAGT) on the Lokomat (Hocoma AG, Volketswil, Switzerland) for 30 minutes, once a day, 5 times a week, for a total of 20 sessions. All subjects were evaluated for general characteristics, the 10-Meter Walk Test (10MWT), the Lower Extremity Motor Score (LEMS), the Functional Ambulatory Category (FAC), the Walking Index for Spinal Cord Injury version II (WISCI-II), the Berg Balance Scale (BBS), and the Spinal Cord Independence Measure version III (SCIM-III) every 0, and 4 weeks. After all the interventions, subjects were stratified using the 10MWT score at 4 weeks into improved group and non-improved group for statistical analysis.

Results

The improved group had younger age and shorter disease duration than the non-improved group. All subjects with the American Spinal Injury Association Impairment Scale level C (AIS-C) tetraplegia belonged to the non-improved group, while most subjects with AIS-C paraplegia, AIS-D tetraplegia, and AIS-D paraplegia belonged to the improved group. The improved group showed greater baseline lower extremity strength, balance, and daily living function than the non-improved group.

Conclusion

Assessment of SCIM-III, BBS, and trunk control, in addition to LEMS, have potential for predicting the effects of robotic treatment in patients with motor incomplete spinal cord injury.

Citations

Citations to this article as recorded by  
  • The Effect of Assistive Robotic Technologies on Quality of Life and Functional Independence in Individuals with Spinal Cord Injury
    Abdurrahim Yıldız, Rüstem Mustafaoğlu, Nur Kesiktaş
    Journal of Basic and Clinical Health Sciences.2024; 8(3): 580.     CrossRef
  • Gait quality after robot therapy compared with physiotherapy in the patient with incomplete spinal cord injured: A systematic review
    Isabella Fabbri, Fabio Betti, Roberto Tedeschi
    eNeurologicalSci.2023; : 100467.     CrossRef
  • Clinical Utility of Robot-Assisted Gait Training in Patients with Spinal Cord Injury Caused by Electrical Burns: A Case Report
    Seung-Yeol Lee, Cheong-Hoon Seo, Yoon-Soo Cho, So-Young Joo
    Journal of Clinical Medicine.2023; 12(23): 7220.     CrossRef
  • Settings matter: a scoping review on parameters in robot-assisted gait therapy identifies the importance of reporting standards
    Florian van Dellen, Rob Labruyère
    Journal of NeuroEngineering and Rehabilitation.2022;[Epub]     CrossRef
  • Feasibility of Overground Gait Training Using a Joint-Torque-Assisting Wearable Exoskeletal Robot in Children with Static Brain Injury
    Juntaek Hong, Jongweon Lee, Taeyoung Choi, Wooin Choi, Taeyong Kim, Kyuwan Kwak, Seongjun Kim, Kyeongyeol Kim, Daehyun Kim
    Sensors.2022; 22(10): 3870.     CrossRef
  • A Survey on Socially Assistive Robotics: Clinicians’ and Patients’ Perception of a Social Robot within Gait Rehabilitation Therapies
    Denniss Raigoso, Nathalia Céspedes, Carlos A. Cifuentes, Antonio J. del-Ama, Marcela Múnera
    Brain Sciences.2021; 11(6): 738.     CrossRef
  • Social Human-Robot Interaction for Gait Rehabilitation
    Nathalia Cespedes, Marcela Munera, Catalina Gomez, Carlos A. Cifuentes
    IEEE Transactions on Neural Systems and Rehabilitation Engineering.2020; 28(6): 1299.     CrossRef
  • Morning Walk®-Assisted Gait Training Improves Walking Ability and Balance in Patients with Ataxia: a Randomized Controlled Trial
    Chul Jung, Dae Yul Kim, Sara Kwon, Min Ho Chun, JaYoung Kim, Sung Hyun Kim
    Brain & Neurorehabilitation.2020;[Epub]     CrossRef
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