Sleep Monitoring and Occlusion-Resistant Fall Detection in Home Care System by Single Depth Camera
Date Issued
2014
Date
2014
Author(s)
Wang, Thun-Hsi
Abstract
Along with the population ageing and birth bust, more and more elderly people need to be cared in their daily living. Considering the acceptance rate and practicability for elderly people, home care systems should work under the conditions that people should not be disturbed by these systems in their daily living. In particular, we focus on the research of sleep behavior and fall event when elderly people are individual at home. Therefore, we propose a sleep monitoring and fall detection system using single depth camera. To calculate correct spatial relationship between human and furniture in an image, a coordinate transformation approach based on depth information and visual angles is used to build up the world coordinate system. By calculating the spatial relationship between human and bed region, people’s sleep behavior and movement on the bed can be recognized precisely. In fall detection, detection methods are mainly composed of motion analysis and posture height. The results of proposed system are 98.4% accuracy rate in in-bed detection and sleep motion detection, and the overall accuracy of fall detection is 96.8%.
Subjects
電腦視覺
深度攝影機
居家看護
睡眠監測
跌倒偵測
Type
thesis
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