步态生物力学大数据分析研究进展
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1.南京体育学院;2.北京体育大学

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Progress of Big Data analysis in Gait Biomechanics
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    摘要:

    目的:学术界和从业人员对大数据分析在步态生物力学中应用的兴趣迅速增长,这促使我们有必要回顾最新的研究进展,以制定新的议程。本文通过提出一种新颖的研究框架来回应这一呼吁,该框架提供了关于步态生物力学环境中应用大数据分析当前文献的全景。方法:本文是以2011-2020年步态生物力学大数据分析相关的科技文献为研究对象,运用内容分析法,从主题结构、层级水平、模型类型和分析技术四个方面进行分析与讨论,并在此基础上对步态生物力学大数据分析未来研究进行展望。结果:围绕大数据分析应用于步态生物力学领域的最新研究成果,首先,从干预和康复、运动训练、假肢设计和评估、了解病因和诊断、了解人移动的特点五个层面分析大数据分析在步态生物力学的应用领域;然后,重点分析和归纳步态生物力学领域大数据分析的层级水平;接着回顾了步态生物力学领域大数据分析的模型和具体技术;最后,总结了大数据分析在步态生物力学领域的未来方向和挑战。结论:全文清晰、全面地展示了目前步态生物力学大数据分析研究的前沿进展,为步态生物力学研究夯实了基础工作,补缺了近年来步态生物力学大数据分析研究综述这一领域的空白。

    Abstract:

    Purpose: The rapidly growing interest from both academics and practitioners towards application of big data analysis in GB has prompted the need to review the up-to-date advances in order to set a new agenda. This paper responds to this call by proposing a novel research framework that provides a panoramic view of the current literature on where and how big data analysis has been applied within the GB context. Methods: Based on the scientific and technological literature related to gait biomechanics by big data analysis from 2011 to 2020 as the research object, this paper uses content analysis method to analyze and discuss from five aspects, including topic structure, analytics level, model type and analysis technology. Results: Firstly,researches on GB field mainly involve five research directions, namely intervention and rehabilitation, exercise training, prosthesis design and evaluation, understanding of etiology and diagnosis, understanding of the characteristics of human movement. Secondly, there is a detailed review of analytics level by year toward GB using big data analytsis. Then, it reviews the models and specific techniques of big data analysis in GB field. Finally, the future directions and challenges of big data analysis in the field of GB are summarized. Conclusion: On this basis, the future research of GB in big data analysis is expected. This paper presents clearly and comprehensively the current advance and development of GB in big data analysis, laying a solid foundation for gait biomechanics research, and filling the gap in the field of GB research review by big data analysis in recent years.

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  • 收稿日期:2020-10-16
  • 最后修改日期:2021-02-10
  • 录用日期:2021-02-18
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