Fall Detection and Alert for Ageing-at-Home of Elderly

Authors:
Xinguo Yu;Xiao Wang;Panachit Kittipanya-Ngam;How Lung Eng;Loong-Fah Cheong
Affiliations:
Institute for Infocomm Research, Singapore 138632;Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117543;Institute for Infocomm Research, Singapore 138632;Institute for Infocomm Research, Singapore 138632;Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117543
Venue:
ICOST '09 Proceedings of the 7th International Conference on Smart Homes and Health Telematics: Ambient Assistive Health and Wellness Management in the Heart of the City
Year:
2009

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Abstract

Fall detection has been an active research problem as fall detection technology is critical for the ageing-at-home of the elderly and it can enhance life safety of the elderly and boost their confidence of ageing-at-home by immediately alerting fall occurrence to care givers. This paper presents an algorithm of fall detection for the ageing-at-home of the elderly. This algorithm detects fall events by identifying (human) shape state change pattern reflecting a fall incident from video recorded by a single fixed camera. The novelty of the algorithm is multiple. First, it detects fall occurrence by identifying the state change pattern. Second, it uses the camera projection matrix in its computing. Thus, it eliminates camera setting-related learning. Lastly, it adds constraints to state change pattern to reduce false alarms. Experiments show that the proposed algorithm has a promising performance.