The growth in the aging population requires caregivers to improve both efficiency and quality of healthcare. In this study, we develop an automated vision-based system for the purpose of supporting monitoring and analysis of the physical and mental well-being of senior citizens. Through collaboration with Haven of Hope Christian Service, we collected video recording data in the care center with surveillance camera. We process and extract personalized facial, activity, and interaction features from the video data using deep-learning-based AI techniques. This integrated health information systems can potentially assist caregivers to gain better insights into the seniors they are taking care of. These insights, including wellness metrics and long-term health pattern of senior citizens, can help caregivers update their caregiving strategies. In this presentation, we will report findings of our analysis and evaluate the system quantitatively. We also outline technical challenges and additional functionalities and technologies needed for offering a comprehensive system.
