UMAFall: Fall Detection Dataset (Universidad de Malaga)
收藏figshare.com2023-05-31 更新2025-03-22 收录
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https://figshare.com/articles/dataset/UMA_ADL_FALL_Dataset_zip/4214283/7
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资源简介：
The
files contain the mobility traces generated by a group of 19 experimental
subjects that emulated a set of predetermined ADL (Activities of Daily Life)
and falls. The traces are aimed at evaluating fall detection algorithms.Several video clips describing the performed movements are also included.The source
and authors of this publicly available dataset should be acknowledged in all
publications in which it is utilized as by referencing any of the following
papers as well as this web-site:
· - Santoyo-Ramón, José Antonio,
Eduardo Casilari, and José Manuel Cano-García. "Analysis of a smartphone-based architecture with multiple mobility
sensors for fall detection with supervised learning." Sensors 18.4 (2018): 1155.
· - Casilari, Eduardo, Jose A.
Santoyo-Ramón, and Jose M. Cano-García. "UMAFall: A Multisensor Dataset for the Research on Automatic Fall
Detection." Procedia Computer Science 110 (2017): 32-39.
该数据集包含由一组19名实验对象生成的移动轨迹文件，这些实验对象模拟了一系列预定的日常生活活动及跌倒场景。这些轨迹旨在评估跌倒检测算法。此外，还包含描述所执行动作的数个视频片段。在使用本公开数据集的所有出版物中，应提及以下论文及本网站以示对数据集来源和作者的认可：
· Santoyo-Ramón, José Antonio, Eduardo Casilari, and José Manuel Cano-García. '基于智能手机的多传感器架构分析及其在跌倒检测中的监督学习应用.' Sensors 18.4 (2018): 1155.
· Casilari, Eduardo, Jose A. Santoyo-Ramón, and Jose M. Cano-García. 'UMAFall: 用于自动跌倒检测研究的多传感器数据集.' Procedia Computer Science 110 (2017): 32-39.
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