Abnormality detection monitoring system for elderly people in sensing and robotic support room

This paper describes an abnormal behavior detection system based on an omni-directional vision sensor as one of the important elements in realizing "sensing and robotic support room" for elderly people. Such support rooms are expected to be further developed in the future with the high performance to automatically recognize elderly people's actions and behavior patterns and detect the unusual patterns using some sensors and to support their daily motions using some robotic manipulator control systems. The proposed monitoring system using an omnidirectional vision sensor automatically learns the daily behavior patterns and detects the unusual behavior patterns and actions using Bayesian network approach. The Bayesian network is constructed using image feature values such as the area and center-of gravity values extracted from the captured image sequence and the respective behavior patterns are represented as the conditional probabilities. Unusual behavior patterns can be automatically detected based on the low generation probability values. Some experiments based on the investigation of elderly people's typical daily behavior patterns show the effectiveness of the proposed system.