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使用佩戴时间来分析消费级可穿戴设备的数据:使用Fitbit数据的案例研究.

Loubna Baroudi1, Ronald Fredrick Zernicke2,3, Muneesh Tewari4,5,6,7

  • 1Department of Mechanical Engineering, University of Michigan-Ann Arbor, 2505 Hayward St, Ann Arbor, MI, 48109, United States, 1 7342626353.

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概括

穿戴设备数据分析需要仔细考虑参与者佩戴时间的遵守. 不一致的磨损时间显著影响步数估计,但心率数据仍然更强大,影响研究问题的可行性.

关键词:
这是Fitbit的Fitbit.行为行为行为行为行为.护理人员 护理人员数据集数据集数据集参与 参与 参与 参与移动健康的移动健康身体活动 身体活动可靠性的可靠性智能手表 智能手表学生 学生 学生 学生使用者使用者使用者使用者走路走路,走路走路,走路走路.磨损时间 磨损时间可穿戴设备可穿戴设备.可穿戴设备可以穿戴.

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科学领域:

  • 数字健康数字健康
  • 人类行为监测监控
  • 可穿戴技术可穿戴技术

背景情况:

  • 消费级可穿戴设备提供了宝贵的真实世界人类行为数据.
  • 保持用户参与度和合规性 (例如,佩戴时间) 是一个重大挑战,导致数据缺口和潜在的"可穿戴设备放弃".

研究的目的:

  • 用不同的人口数据集量化磨损时间要求对研究结果的影响.
  • 强调在分析消费级可穿戴设备数据时,需要考虑参与者穿戴时间的必要性.
  • 确定所有研究问题是否需要相同的佩戴时间遵守.

主要方法:

  • 分析了来自6个不同人群样本 (护理人员,学生,儿科瘤患者) 的3个Fitbit数据集.
  • 评估了平均每日步数和心率对不同磨损时间定义的敏感性 (目标1).
  • 评估研究以较低的合规性样本质疑可行性,重点关注平均每日步数和步行时的平均心率 (目标2).

主要成果:

  • 根据分析方法和磨损时间的遵守,人口平均每日步数估计变化高达2000步.
  • 低磨损时间 (<15小时/天) 的样本对分析方法的变化表现出最高的灵敏度;个别步数差异在参与者的子集中超过1000-3000步.
  • 平均每日心率估计很强大,可以承受时间变化;一些有足够数据的个人在行走时心率缺乏足够的数据每日步数.

结论:

  • 证明了消费级可穿戴设备的参数估计与参与者佩戴时间之间的直接关系.
  • 强调彻底的磨损时间分析对于确保可穿戴设备数据发现的相关性和可靠性至关重要.