# Fall Detection Approaches for Monitoring Elderly HealthCare Using Kinect Technology: A Survey
## 6 Kinect Datasets for Fall Detection  
The creation of rich and well annotated datasets is one of the compulsory elements for detecting falls by computer vision. These datasets are made up of video sequences of fall and ADL events. The datasets are intended initially to assess the success of the algorithms. Many researchers have made their datasets public within the scientific community in order to compare more judicious approaches and raise new challenges. Many of the current fall detection benchmark datasets are performed in simulated scenarios [118]. Table 5 summarizes the public Kinect datasets usable for fall detection, while Table 6 enumerates the types of scenarios and provides the access links for each database. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  
The fall detection dataset created by [PERSON] and [PERSON] (ZZ-VA dataset) [101] contains data collected from two viewpoints. It was collected using two version 1 Kinects located at two corners of a simulated apartment. Six subjects performed the experimental actions in the Heracleia Human-Centered Computing Laboratory at the \begin{table}
\begin{tabular}{l l l} \hline \hline
**Dataset** & **Types of Events** & **Available from (\({}^{\star}\))** \\ \hline  & Real falls & \\  & Picking up object from the ground & \\  & Tying Diseases & \\  & Setting-lying on the floor & \\  & Living down-Jumping on the bed & \\  & Opening-Closing a drawer at ground level & \\ \hline  & Falls & \\  & Picking up object from the ground & \\  & Setting on the ground & \\ \hline  & Totally occuled falls & \\  & un-occluded picking up something from the ground & \\  & un-occluded sitting on the ground & \\  & un-occluded tying shoelaces & \\  & lying down on the ground (end frame is totally occluded) & \\ \hline  & Falling down & \\  & Bending & \\  & Squating & \\  & Siting & \\  & Walking & \\ \hline  & Falls from standing & \\  & Falls from sitting on the chair & \\  & Walking & \\  & Siting down & \\ \hline  & Living on the floor & \\  & Lying on bed/sofa & \\  & Bending to take or put an object from the floor & \\  & Ting laces & \\  & Crrouching down & \\ \hline  & Falls from standing & \\  & Falls from sitting on the chair & \\  & Walking & \\ \hline  & Fall forward and ends up lying / sitting & \\  & Fall lateral and ends up lying & \\  & Fitting on a chair & \\  & Walking and Picking an object from the floor & \\  & Walking back and forth & \\  & lying down on the floor & \\ \hline  & Fall forward when (trying-always) to sit on a chair & \\  & with and without rotation & \\  & Fall lateral when(trying-always) to sit on a chair & \\  & without rotation & \\  & Fall forward-backward when trying to sit on the & \\  & floor with and without rotation & \\  & Fall forward-backward from standing with and & \\  & without rotation & \\  & Fall lateral without rotation & \\  & Fall forward when walking with and without rotation & \\  & Fall forward against the wall without rotation & \\  & Fall lateral from (trying-always) lying on a bed & \\ \hline  & without rotation & \\  & Setting down on a chair + slowlySitting down on the floor + slowly & \\  & Rising from a sitting position on a chair-the floor & \\  & Rising from a lying position on the floor-a bed & \\  & Rising from one’s knees-crouching position & \\  & Lying down on a bed-on the floor & \\  & Kneeling-Crouching down on the floor & \\  & Standing still & \\  & Bending to pick up an object from the floor & \\  & Stretching & \\  & Shifting from one foot to the other & \\  & Resting against the wall & \\  & Stumbling while walking with recovery & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Descriptive table of public Kinect datasets for fall detection. University of Texas at Arlington. This dataset includes 26 reals falls from the two viewpoints and 61 fall-like events; in all, 31,614 depth frames are registered at 320 \(\times\) 240 pixel resolution. Experimental scenarios from the two Kinects are not captured at the same moment.