Fall Prevention and Detection in Smart Homes Using Monocular Cameras and an Interactive Social Robot
Killian Lachaux, Julien Maítre, Kévin Bouchard, Maxime Lussier, Carolina Bottari, Mélanie Couture, Nathalie Bier, Sylvain Giroux, Gaboury Sebastien
Abstract
Falls are one of the greatest risks for older adults living at home. They are also one of the biggest factors impacting independence and quality of life. Falling and even the fear of falling can lead to serious physical and mental health issues. Moreover, some afflictions like the self-neglect syndrome make this risk even greater. In this paper, we introduce a system to manage the fall risk before and after it happens, using monocular cameras and an humanoid robot. The proposed system achieves a 75% detection of trip-hazard objects in a heavily cluttered environment, and an 86.11% accuracy in detecting falls after they happened.