UMAFall: Fall Detection Dataset (Universidad de Malaga)

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.

搜集汇总

背景与挑战

背景概述

UMAFall数据集是一个用于跌倒检测研究的多传感器数据集，包含19名实验对象的移动轨迹数据和视频片段，旨在支持跌倒检测算法的开发和评估。数据集由西班牙马拉加大学等机构资助，并已在多篇研究论文中被引用。