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.<br>