Chameleon: personalised and adaptive fall detection of elderly people in home-based environments

: Threshold-based fall detection has been widely adopted in conventional fall detection systems. In this paper, we argue that a fixed threshold is not flexible enough for different people. By exploiting the personalised and adaptive threshold, we propose a novel threshold extraction model, which meets being adaptive to detect a fall, while only taking consideration of data from activity of daily living (ADL). We believe this is a solid step toward improving the performance of the threshold-based fall detection solution. Furthermore, we incorporate the proposed idea into Chameleon. To evaluate the performance of this threshold extraction model, we compared Chameleon with advanced magnitude detection (AMD) and fixed and tracking fall detection (FTFD). The results

• Type: Journal
• Year: 2016
• Where: IJSNET
• Authors: Lingmei Ren, Weisong Shi
• Keywords: IJSNET 2016