Title:	AN AUTOMATED MULTI-SENSOR MONITORING SYSTEM OF ELDERLY HOMECARE CLIENT'S ACTIVITY PATTERNS
Author(s):	Sean T. Doherty, Diane Doran, Rafik A. Goubran
ISBN:	978-972-8939-49-6
Editors:	Mário Macedo
Year:	2011
Edition:	Single
Keywords:	Elderly, remote monitoring, daily activities, sleep, decision support
Type:	Poster/Demonstration
First Page:	262
Last Page:	264
Language:	English
Cover:
Full Contents:	click to dowload
Paper Abstract:	There is an increasing need to provide home care support to the growing elderly population who want to live independently in their homes as they age. In Canada, homecare expenditure is the second fastest growing segment of the publicly funded healthcare system (after medication expenditures), and demographic trends suggest these costs will escalate significantly over the next two decades. A large percentage of homecare clients live alone and are visited only a few times per week by health providers. This isolation poses unique challenges for health service delivery, including the coordination of information and communication among providers, as well as monitoring of patient status and safety between visits. The purpose of this poster is to present an automated activity monitoring system of home care clients as they go about their daily lives. The focus is on the technological development and challenges based on a multi-disciplinary research project and pilot test. The method involves a unique combination of two technologies: a Bed Pressure Sensitive Mat (BPSM) installed in the bedroom, and a Global Positioning System (GPS) receiver plus 3-axis accelerometer worn by patients during waking hours (embedded in a BlackBerry). This poster will demonstrate how these combined technologies provide a comprehensive 24-hour automated and wireless monitoring of patient's in-bed, in-home, and out-of-home active and sedentary activities. Our recommendation based on focus group discussion with clinicians is to seamlessly present this information as a 24 hour time line or "diary" of events, or as graphically summaries of time spent in various activity types over given day, week or longer. We recommend that this information be presented as part of a graphical user interface on a mobile computer to support a point-of-care decision support system for home health care providers. We expect that the homecare environment of the future would be well served by monitoring technologies that are as passive as possible and do not overload patients or their home with multiple devices.
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