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Updated: Jun 23, 2025

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Experimental Methods to Study Human Postural Control
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在理解姿势控制方面使用非线性分析:一个范围审查
Suellen de Oliveira Veronez1, Caroline Cunha do Espirito-Santo2, André Felipe Oliveira de Azevedo Dantas2
1Department of Physiotherapy, College of Health and Sport Science, Universidade do Estado de Santa Catarina (UDESC), Florianópolis, SC, Brazil; Neuroscience Graduate Program, Universidade Federal de Santa Catarina (UFSC), Florianópolis, SC, Brazil.
Human movement science
|June 21, 2024
概括
非线性分析,特别是样本,被广泛用于研究姿势控制动态. 本综述确定了91种用于静静站立,动态任务和步态的算法,有助于未来的研究.
科学领域:
- 生物力学和运动控制
- 生理学动力学是什么
- 在人类运动中的数据分析.
背景情况:
- 非线性分析提供了对姿势控制复杂动态的深入洞察.
- 在全面了解在姿势控制研究中应用的各种非线性测量方法方面存在挑战.
- 关于姿势控制中的非线性分析的现有文献需要系统的总结和传播.
研究的目的:
- 识别和分类用于姿势控制研究的非线性分析方法.
- 总结和传播关于非线性分析应用在动态和安静的姿势任务中的文献.
- 为未来的姿势控制复杂性和相互作用的研究方向提供见解.
主要方法:
- 根据PRISMA扩展范围审查 (PRISMA-ScR) 准则进行了范围审查.
- 在主要数据库 (PubMed/Medline,Embase,CINAHL,Web of Science,Google Scholar) 进行了搜索,截至2023年7月.
- 包括397个独特的研究,分析使用的非线性算法和姿势任务.
主要成果:
- 确定了91个不同的非线性算法,主要分为基于的,基于分数的,递归量化和稳定量化.
- 静静地站立是最受研究的条件 (28%的基于的分析),其次是动态站立和步行任务.
- 样本是最常用的算法,在43%的审查研究中应用.
结论:
- 非线性分析,特别是像样本一样的度,是研究姿势控制机制的普遍工具.
- 该审查强调了方法和应用的多样性,为标准化方法提供了基础.
- 这些发现指导了未来的研究,阐明了姿势控制系统在各种任务需求中的复杂性和相互作用.
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