Monitoring Personal Safety by Unobtrusively Detecting Unusual Periods of Inactivity

摘要

Due to the ageing of the world population, a growing number of elderly people remain in their homes, requiring different levels of care. Our formative user studies show that the main concern of elderly people and their families is "fall detection and safe movement in the house", while eschewing intrusive monitoring devices. This paper introduces a statistical model based on non-intrusive sensor observations that posits whether a person is not safe by identifying unusually long periods of inactivity within different regions in the home. Evaluation on two real-life datasets shows that our system outperforms a state-of-the-art system.