DocumentCode :
1841079
Title :
Intelligent Video Monitoring to Improve Safety of Older Persons
Author :
Datong Chen ; Bharucha, A.J. ; Wactlar, H.D.
Author_Institution :
Carnegie Mellon Univ., Pittsburgh
fYear :
2007
fDate :
22-26 Aug. 2007
Firstpage :
3814
Lastpage :
3817
Abstract :
This paper presents the application of computer vision and machine learning technologies to a clinical task of paramount importance, improving safety of older persons. We propose an intelligent monitoring system equipped with a camera network and an automatic elopement detection algorithm to reduce the risks of un-witnessed elopements from a dementia unit in order to avoid their potential catastrophic consequences. The camera network employs 23 cameras to record daily activities in our test bed, which includes 15 residents, 4 registered and licensed practical nurses and a number of certified nursing assistants. An elopement detector is then built by using computer vision algorithms and a machine learning algorithm to automatically detect elopements and alert caregivers. The experiments demonstrate that the proposed system leverages the advantages of monitoring from multiple cameras and is able to detect elopements with almost 100% accuracy.
Keywords :
behavioural sciences; computer vision; geriatrics; learning (artificial intelligence); patient monitoring; video cameras; automatic elopement detection algorithm; camera network; computer vision application; dementia; elopement detector; intelligent video monitoring; machine learning technology; old person safety; Application software; Cameras; Computer vision; Computerized monitoring; Intelligent networks; Intelligent systems; Learning systems; Machine learning; Machine learning algorithms; Safety; Activities of Daily Living; Aged; Aged, 80 and over; Algorithms; Dementia; Female; Homes for the Aged; Humans; Male; Monitoring, Physiologic; Pattern Recognition, Automated; Safety; Television;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
ISSN :
1557-170X
Print_ISBN :
978-1-4244-0787-3
Type :
conf
DOI :
10.1109/IEMBS.2007.4353163
Filename :
4353163
Link To Document :
بازگشت