  A new application for real-time monitoring of the lack of movement in older
adults' own homes is proposed, aiming to support people's lives and
independence in their later years. A lightweight camera monitoring system,
based on an RGB-D camera and a compact computer processor, was developed and
piloted in community homes to observe the daily behavior of older adults.
Instances of body inactivity were detected in everyday scenarios anonymously
and unobtrusively. These events can be explained at a higher level, such as a
loss of consciousness or physiological deterioration. The accuracy of the
inactivity monitoring system is assessed, and statistics of inactivity events
related to the daily behavior of older adults are provided. The results
demonstrate that our method achieves high accuracy in inactivity detection
across various environments and camera views. It outperforms existing
state-of-the-art vision-based models in challenging conditions like dim room
lighting and TV flickering. However, the proposed method does require some
ambient light to function effectively.
