Design of a home-based machine vision system to monitor the functional health of an occupant.
Published: 2005
Language: eng
Number of pages: 139
Description: To support the growing elderly population in Canada who want to age-in-place, techniques and algorithms have been developed to monitor functional health in the home environment. A health monitoring system has been developed with machine vision and pattern analysis components to track the occupant, learn his/her pattern of activity, and detect significant deviations that several research groups have shown could indicate a change in health status. The effectiveness of the health monitoring system was investigated with a pilot study capturing video footage of a 28-day simulation including 21-days of normal activity and seven days of abnormal activity. The system was effective in learning an occupant's pattern of activity and detecting significant deviations that were indicative of changes in the occupant's functional health status. Overall, the results show that a health monitoring system could be developed that uses machine vision and basic artificial intelligence with promising potential to support aging-in-place.
Notes: Source: Masters Abstracts International, Volume: 44-02, page: 0961.

Thesis (M.H.Sc.)--University of Toronto, 2005.

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