跌倒风险评估数据集:年长的成年参与者接受了时间上升和去测试
Wisanu Jutharee1, Chatchai Paengkumhag2, Warissara Limpornchitwilai2
1Institute of Field Robotics and Automation, King Mongkut's University of Technology Thonburi, Bangkok, Thailand.
Data in brief
|October 23, 2023
概括
本研究介绍了一组数据,用于在时间上升和移动 (TUG) 测试期间使用惯性测量单元 (IMU) 传感器评估老年人跌倒风险. 这些数据可以帮助开发针对个性化的防摔策略的预测模型.
科学领域:
- 老年学是一门学科.
- 生物医学工程 生物医学工程
- 数据科学数据科学数据科学
背景情况:
- 评估老年人跌倒风险对于预防受伤至关重要.
- 时间起床和起床 (TUG) 测试是一种常见的临床评估,用于移动性和跌倒风险.
- 惯性测量单元 (IMU) 传感器为运动分析提供客观,定量数据.
研究的目的:
- 为老年人进行跌倒风险评估提供全面的数据集.
- 促进用于降落风险检测的预测模型的开发.
- 为了能够调查健康行为和跌倒风险之间的关系.
主要方法:
- 从腰部佩戴的IMU传感器 (三轴加速度和陀螺仪) 收集的信号数据.
- 向34名老年成年参与者进行TUG测试.
- 处理IMU原始数据,提取步行时间并应用低通过.
主要成果:
- 一个结构化数据集,包含参与者信息和从TUG测试中处理的IMU信号数据.
- 数据集包括个人,行为和健康相关数据以及传感器信号.
- 专家的观察结果被收集,以告知潜在的跌倒风险模型的发展.
结论:
- 该数据集为开发先进的跌倒风险检测模型提供了宝贵的资源.
- 调查参与者数据和跌倒风险之间的相关性可以为个性化干预提供信息.
- 这一数据集支持针对老年人的定制治疗和康复计划的研究.
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