在ARIC研究中,比较ARIC研究中老年人高分辨率手腕加速度计数据的步数算法
Sunan Gao1, Xinkai Zhou2, Lily Koffman2
1Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.
概括
五个开源的步数计数算法在老年人中显示出高相关性. 虽然总步骤有所不同,但标准化结果与健康结果相似,强调为临床使用选择算法.
科学领域:
- 老年学是一门学科.
- 生物医学工程 生物医学工程
- 公共卫生 公共卫生
背景情况:
- 手腕加速度计是身体活动研究的关键.
- 开源算法存在用于步数计数,但对老年人来说需要进行比较.
研究的目的:
- 用手腕加速度计数据比较五个开源的步数计数算法.
- 为老年人提供算法使用建议.
主要方法:
- 1282名参与者 (平均年龄为83.4岁) 佩戴了ActiGraph GT9X设备7天.
- 五种算法 (ADEPT,Oak,SDT,Verisense,Stepcount) 应用于80Hz三轴加速度计数据.
- 分析了步数分布和与健康结果的关联.
主要成果:
- 平均每天的步数在各个算法 (988-23,607步) 中有显著差异.
- 所有算法都显示出强烈的相关性 (r=0.52-0.96) 和在z-scoring后与健康结果的类似关联.
- 步数随着年龄的增长而下降 (119.0-142.8步/年).
结论:
- 步数算法高度相关,在标准化后显示出类似的健康关联.
- 原始步数的广泛变化需要对老年人进行仔细的算法选择.
- 算法选择对健康监测和临床应用的解释产生影响.
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