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Evaluation of the improvement of walking ability in patients with spinal cord injury using lower limb rehabilitation robots based on data science

Spinal cord injury (SCI) is a serious disabling injury, and the main factors causing SCI in patients include car accidents, falls from heights, as well as heavy blows and falls. These factors can all cause spinal cord compression or even complete rupture. After SCI, problems with the movement, balan...

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Autores principales: Zhao, Hui, Yang, Jingyi, Yang, Jie, Jiang, Hongying, Qin, Yecai, Lei, Qian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: De Gruyter 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638838/
https://www.ncbi.nlm.nih.gov/pubmed/37954153
http://dx.doi.org/10.1515/tnsci-2022-0320
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author Zhao, Hui
Yang, Jingyi
Yang, Jie
Jiang, Hongying
Qin, Yecai
Lei, Qian
author_facet Zhao, Hui
Yang, Jingyi
Yang, Jie
Jiang, Hongying
Qin, Yecai
Lei, Qian
author_sort Zhao, Hui
collection PubMed
description Spinal cord injury (SCI) is a serious disabling injury, and the main factors causing SCI in patients include car accidents, falls from heights, as well as heavy blows and falls. These factors can all cause spinal cord compression or even complete rupture. After SCI, problems with the movement, balance, and walking ability of the lower limbs are most common, and SCI can cause abnormalities in patient’s movement, sensation, and other aspects. Therefore, in the treatment of SCI, it is necessary to strengthen the rehabilitation training (RT) of patients based on data science to improve their motor ability and play a positive role in the recovery of their walking ability. This article used lower limb rehabilitation robot (LLRR) to improve the walking ability of SCI patients and applied them to SCI rehabilitation. The purpose is to improve the limb movement function of patients by imitating and assisting their limb movements, thereby achieving pain relief and muscle strength enhancement and promoting rehabilitation. The experimental results showed that the functional ambulation category (FAC) scale scores of Group A and Group B were 0.79 and 0.81, respectively, in the first 10 weeks of the experiment. After 10 weeks of the experiment, the FAC scores of Group A and Group B were 2.42 and 4.36, respectively. After the experiment, the FAC score of Group B was much higher than that of Group A, indicating that Group B was more effective in improving patients’ walking ability compared to Group A. This also indicated that LLRR rehabilitation training can enhance the walking ability of SCI patients.
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spelling pubmed-106388382023-11-11 Evaluation of the improvement of walking ability in patients with spinal cord injury using lower limb rehabilitation robots based on data science Zhao, Hui Yang, Jingyi Yang, Jie Jiang, Hongying Qin, Yecai Lei, Qian Transl Neurosci Research Article Spinal cord injury (SCI) is a serious disabling injury, and the main factors causing SCI in patients include car accidents, falls from heights, as well as heavy blows and falls. These factors can all cause spinal cord compression or even complete rupture. After SCI, problems with the movement, balance, and walking ability of the lower limbs are most common, and SCI can cause abnormalities in patient’s movement, sensation, and other aspects. Therefore, in the treatment of SCI, it is necessary to strengthen the rehabilitation training (RT) of patients based on data science to improve their motor ability and play a positive role in the recovery of their walking ability. This article used lower limb rehabilitation robot (LLRR) to improve the walking ability of SCI patients and applied them to SCI rehabilitation. The purpose is to improve the limb movement function of patients by imitating and assisting their limb movements, thereby achieving pain relief and muscle strength enhancement and promoting rehabilitation. The experimental results showed that the functional ambulation category (FAC) scale scores of Group A and Group B were 0.79 and 0.81, respectively, in the first 10 weeks of the experiment. After 10 weeks of the experiment, the FAC scores of Group A and Group B were 2.42 and 4.36, respectively. After the experiment, the FAC score of Group B was much higher than that of Group A, indicating that Group B was more effective in improving patients’ walking ability compared to Group A. This also indicated that LLRR rehabilitation training can enhance the walking ability of SCI patients. De Gruyter 2023-11-11 /pmc/articles/PMC10638838/ /pubmed/37954153 http://dx.doi.org/10.1515/tnsci-2022-0320 Text en © 2023 the author(s), published by De Gruyter https://creativecommons.org/licenses/by/4.0/This work is licensed under the Creative Commons Attribution 4.0 International License.
spellingShingle Research Article
Zhao, Hui
Yang, Jingyi
Yang, Jie
Jiang, Hongying
Qin, Yecai
Lei, Qian
Evaluation of the improvement of walking ability in patients with spinal cord injury using lower limb rehabilitation robots based on data science
title Evaluation of the improvement of walking ability in patients with spinal cord injury using lower limb rehabilitation robots based on data science
title_full Evaluation of the improvement of walking ability in patients with spinal cord injury using lower limb rehabilitation robots based on data science
title_fullStr Evaluation of the improvement of walking ability in patients with spinal cord injury using lower limb rehabilitation robots based on data science
title_full_unstemmed Evaluation of the improvement of walking ability in patients with spinal cord injury using lower limb rehabilitation robots based on data science
title_short Evaluation of the improvement of walking ability in patients with spinal cord injury using lower limb rehabilitation robots based on data science
title_sort evaluation of the improvement of walking ability in patients with spinal cord injury using lower limb rehabilitation robots based on data science
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638838/
https://www.ncbi.nlm.nih.gov/pubmed/37954153
http://dx.doi.org/10.1515/tnsci-2022-0320
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