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基于数字人体运动模型的运动治疗慢性病效果评估研究。

A Study on the Evaluation of the Effect of Exercise on the Treatment of Chronic Diseases Based on a Digital Human Movement Model.

机构信息

College of Physical Education, China West Normal University, NanChong 637000, China.

出版信息

J Healthc Eng. 2022 Jan 31;2022:1984145. doi: 10.1155/2022/1984145. eCollection 2022.

Abstract

The aim of this study was to summarise the therapeutic effects of exercise interventions for common chronic diseases and to analyse the scope of application and problems of various exercise treatment protocols, with a view to guiding clinical practice and providing references for subsequent research. To this end, this paper describes how to extract feature parameters for gait analysis based on a digital human motion model. In-depth descriptions of the extraction algorithms for spatiotemporal features, centre-of-mass movement features, joint mobility, and joint contact forces are presented, and the reliability of the knee contact force extraction algorithm is analysed in particular. To analyse the effect of exercise on the treatment of chronic diseases, 50 cases of elderly chronic disease patients collected from the community were selected and subjected to healthy exercise for 1 year, before and after the healthy exercise. After the exercise, the elderly chronic disease patients' blood pressure, lipid, and blood glucose attainment rates, chronic diseases, and knowledge of nonpharmacological treatments were significantly higher, with statistically significant differences compared to the preexercise period ( < 0.05).

摘要

本研究旨在总结运动干预常见慢性病的治疗效果,并分析各种运动治疗方案的应用范围和存在的问题,以期为临床实践提供指导,并为后续研究提供参考。为此,本文描述了如何基于数字人体运动模型提取步态分析的特征参数。详细介绍了时空特征、质心运动特征、关节活动度和关节接触力的提取算法,并特别分析了膝关节接触力提取算法的可靠性。为了分析运动对慢性病治疗的影响,从社区中选取 50 例老年慢性病患者,进行 1 年的健康运动,在健康运动前后分别进行了测试。运动后,老年慢性病患者的血压、血脂和血糖达标率、慢性病及非药物治疗知识明显提高,与运动前相比差异有统计学意义( < 0.05)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa5e/8820862/9cc2862b2e97/JHE2022-1984145.001.jpg

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