Application of k Nearest Neighbors Approach to the Fall Detection of Elderly People Using Depth-Based Sensors

This paper presents the methodology of the elderly people's fall detection using the k Nearest Neighbors (kNN) as the decision making module. The problem of the data acquisition by the depth sensors and feature selection for this task is introduced. The classification problem is discussed. The decision making algorithm and its parameters are briefly described. Experimental results based on data collected in the laboratory are presented and commented. The paper is concluded with future prospects of the approach and its possible modifications.