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相关概念视频

Survival Tree01:19

Survival Tree

84
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
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基于手腕的摔倒检测:在数据集中通用化.

Vanilson Fula1, Plinio Moreno1,2

  • 1Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal.

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概括
此摘要是机器生成的。

这项研究通过结合三个现有的数据集,创建了一个更大的落检测数据集. 新的数据集提高了老年人跌倒检测的准确性,减少了假阳性.

关键词:
落检测系统的系统.这是错误的警报.滑动窗户是一个滑动窗户.不平衡的学习学习.手腕设备是一种手腕设备.

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科学领域:

  • 老年学是指老年学的学科.
  • 生物医学工程 生物医学工程
  • 机器学习 机器学习

背景情况:

  • 跌倒是导致老年人独立性下降和医疗费用大幅增加的主要原因.
  • 现有的摔倒检测系统通常使用有限的数据集,导致不良的概括和高的假阳性率.
  • 需要更强大,更全面的数据集来训练可靠的摔倒检测模型.

研究的目的:

  • 通过整合来自三个不同的来源的数据,开发一个新的,更大的数据集用于摔倒检测.
  • 建立一个标准化的方法来整合未来的数据集,增强可扩展性.
  • 通过成本敏感的机器学习技术来评估组合数据集的有效性.

主要方法:

  • 通过合并三个现有数据集,创建了一个新的数据集,产生了1300多个落样本和28000个非落样本.
  • 从加速度计和陀螺仪数据中提取时间和频率特征,使用2秒的滑动窗口与50%的重叠.
  • 使用成本敏感的机器学习模型来解决落检测数据中固有的阶级失衡问题.

主要成果:

  • 综合数据集与单个数据集相比,显示出优越的概括能力.
  • 开发的模型实现了高性能指标:90.57%的回忆率,96.91%的特异性和98.85%的ROC曲线下的面积 (AUC-ROC).
  • 该模型有效地区分了日常活动和秋季活动.

结论:

  • 拟议的综合数据集显著提高了落检测系统的性能和可靠性.
  • 这种方法解决了小型单一源数据集的局限性,为更准确的现实应用铺平了道路.
  • 开发的数据集和方法提供了一个可扩展的解决方案,用于改善老龄化人口中防摔策略.