Fuzzy inference based non-daily behavior pattern detection for elderly people monitoring system.
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 omni-directional vision sensor automatically learns the daily behavior patterns and detects the unusual behavior patterns and actions using fuzzy inference approach. The fuzzy rules are constructed using image feature values such as the area and center-of gravity values extracted from the captured image sequence and their patterns appearance frequency. Unusual behavior patterns can be automatically detected based on the possibility distribution inference method. Some experiments based on the investigation of elderly people's typical daily behavior patterns show the effectiveness of the proposed system.
Seki
Hirokazu
H
Department of Electrical, Electronics and Computer Engineering, Chiba Institute of Technology, Chiba, 275-0016, Japan. seki.hirokazu@it-chiba.ac.jp
D056044:Actigraphy / Q000379:methods*; D000203:Activities of Daily Living; D000369:Aged, 80 and over; D000465:Algorithms; D005260:Female; D016330:Frail Elderly; D017143:Fuzzy Logic; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D018670:Monitoring, Ambulatory / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*