Development of an intrinsic health risk prediction model for camera-based monitoring of older adults living alone

Abstract

Due to the recent COVID-19 pandemic, drastic changes in the social service system for the care and safety of vulnerable social groups are urgently required in South Korea. It is interesting whether welfare technology can temporarily replace or supplement traditional care services, originally performed by trained human resources and further can be applied in a closed and non-contact living space. Therefore, efforts are being made to converge various intelligent information technologies such as artificial intelligence, robots, and IoT in care services. Considering the limitations of the "National Emergency Notification System,” which was first implemented for older adults living alone in Korea, we performed to establish a monitoring system that can measure health-threatening behaviors, social isolation, and self-neglect of older adults living alone using RGB video data and the latest deep learning methodologies. We would like to suggest future applicability of welfare technology, which can aid in active health care management instead of just simple monitoring. Such a welfare technology can provide a new alternative form of social service to increasing aging population in single-person households and to overcome changes in elder care environment