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Медицинская библиотека · Journal of musculoskeletal & neuronal interactions · 2024

Effect of Upper Limb Repetitive Facilitative Exercise on Gait of Stroke Patients based on Artificial Intelligence and Computer Vision Evaluation.

Song Caiping, Wang Lingcong, Ding Jianhui, Xu Cui, Yang Hang, Mao Yajun

СтатьяРандомизированное исследованиеПеревод пока не подготовлен

Аннотация

OBJECTIVE

This study aims to assess how enhancing upper limb function on the affected side of stroke influences the gait of the lower limb.

METHODS

Forty eligible stroke patients were randomly assigned to either a control group or a treatment group, with 20 patients in each group. Both groups underwent dynamic evaluation using artificial intelligence and computer vision before treatment. This evaluation focused on analyzing the range of motion of the shoulder and elbow during the gait cycle, as well as various gait parameters (such as step length, step speed, and percentage of stance phase) on the affected side. Following evaluation, the control group received routine rehabilitation treatment.

RESULTS

The results indicated that there was no significant difference between the two groups before treatment. However, following treatment, there was a notable improvement in the motion of the shoulder and elbow joints on the affected side among patients in the treatment group (p<0.05), whereas the control group showed only slight improvement, which was not statistically significant (p>0.05).

CONCLUSION

The improvement in upper limb function on the affected side also appears to positively influence gait recovery. However, it's important to note that the observation period was relatively short. Further studies are needed to confirm whether this effect is sustained over the long term.

Для цитирования: Song Caiping, Wang Lingcong, Ding Jianhui, Xu Cui, Yang Hang, Mao Yajun. Effect of Upper Limb Repetitive Facilitative Exercise on Gait of Stroke Patients based on Artificial Intelligence and Computer Vision Evaluation.. Journal of musculoskeletal & neuronal interactions. 2024.

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