Activity Identification, Classification, and Representation of Wheelchair Sport Court Tasks: A Method Proposal.

IF 2.3 Q3 BIOCHEMICAL RESEARCH METHODS
Mathieu Deves, Christophe Sauret, Ilona Alberca, Lorian Honnorat, Yoann Poulet, Arnaud Hays, Arnaud Faupin
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引用次数: 0

Abstract

Background: Monitoring player mobility in wheelchair sports is crucial for helping coaches understand activity dynamics and optimize training programs. However, the lack of data from monitoring tools, combined with a lack of standardized processing approaches and ineffective data presentation, limits their usability outside of research teams. To address these issues, this study aimed to propose a simple and efficient algorithm for identifying locomotor tasks (static, forward/backward propulsion, pivot/tight/wide rotation) during wheelchair movements, utilizing kinematic data from standard wheelchair mobility tests.

Methods: Each participant's wheelchair was equipped with inertial measurement units-two on the wheel axes and one on the frame. A total of 36 wheelchair tennis and badminton players completed at least one of three proposed tests: the star test, the figure-of-eight test, and the forward/backward test. Locomotor tasks were identified using a five-step procedure involving data reduction, symbolic approximation, and logical pattern searching.

Results: This method successfully identified 99% of locomotor tasks for the star test, 95% for the figure-of-eight test, and 100% for the forward/backward test.

Conclusion: The proposed method offers a valuable tool for the simple and clear identification and representation of locomotor tasks over extended periods. Future research should focus on applying this method to wheelchair court sports matches and daily life scenarios.

轮椅运动场任务的活动识别、分类和表示:方法建议。
背景:监测轮椅运动中运动员的活动能力对于帮助教练了解活动动态和优化训练计划至关重要。然而,由于缺乏来自监测工具的数据,再加上缺乏标准化的处理方法和无效的数据展示,限制了这些工具在研究团队之外的可用性。为了解决这些问题,本研究旨在利用标准轮椅移动测试的运动学数据,提出一种简单高效的算法,用于识别轮椅移动过程中的运动任务(静态、向前/向后推进、枢轴/紧/宽旋转):每位参赛者的轮椅都配有惯性测量单元--两个在轮轴上,一个在车架上。共有36名轮椅网球和羽毛球运动员完成了三项测试中的至少一项:星形测试、八字形测试和前进/后退测试。运动任务的识别分为五个步骤,包括数据还原、符号近似和逻辑模式搜索:结果:该方法成功识别了 99% 的星形测试运动任务、95% 的八字形测试运动任务和 100% 的前进/后退测试运动任务:结论:所提出的方法为简单明了地识别和表示长时间的运动任务提供了有价值的工具。未来的研究应侧重于将该方法应用于轮椅球场运动比赛和日常生活场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Methods and Protocols
Methods and Protocols Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (miscellaneous)
CiteScore
3.60
自引率
0.00%
发文量
85
审稿时长
8 weeks
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