Automated Vision-Based Wellness Analysis for Elderly Care Centers

Abstract

The growth in the aging population require caregivers to improve both efficiency and quality of healthcare. In this study, we develop an automatic, vision-based system for monitoring and analyzing the physical and mental well-being of senior citizens. Through collaboration with Haven of Hope Christian Service, we collect video recording data in the care center with surveillance camera. We then process and extract personalized facial, activity, and interaction features from the video data using deep neural networks. This integrated health information systems can assist caregivers to gain better insights into the seniors they are taking care of. We report findings of our analysis and evaluate the system quantitatively to demonstrate the effectiveness.