Fall prevention using head velocity extracted from visual based VDO sequences
Nuth Otanasap, Poonpong Boonbrahm · 2014
More than ten millions elderly people fall each year. Falls are the important cause of injury related to death and set of symptoms. Most of "fall detection" systems are focused on critical and post-fall phase which mean that the faller may already be injured. In this study, we propose an early fall detection in critical fall phase using velocity characteristics, collected by Kinect sensor with 30 frames per second. A series of normal and falling activities were performed by 5 volunteers in first experiment and 11 volunteers in second experiment. The fall velocity based point was calculated by the first experiment as 50 postures, 2210 frames recorded.