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The majority of the growing elder population, in the US and the rest of the world, requires some degree of formal and/or informal care either due to loss of function or failing health as a result of aging. According to findings of the Center for Disease Control, nearly three quarters of elders over the age of 65 suffer of one or more chronic diseases. The cost and burden of caring for elders is steadily increasing. If given the choice, many elders would prefer to lead an independent way of life in a residential setting with minimum intervention from the caregiver (i.e. to age in place).
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On the other hand, the role of informal caregivers in providing care to the elder population has greatly increased over the past two decades in the US, due to change in the Medicare system, and has resulted in shifting the responsibility for care during recuperation, rehabilitation, and long-term disability from institutions to individuals and families in the community. Consequently, informal caregivers have come to be viewed as “nurse-extenders”, providing most of the nursing care to elders in long-term care. In fact, national data bases derived from different sources have provided unequivocal evidence that family and friends are the sole care providers for about three quarters of all community-dwelling elders.
The shift of long-term elder care responsibility to informal caregivers has increased their physical, financial burdens and emotional strains. A national study reports that 15% of caregivers admit to having physical or emotional health problems directly related to caregiving and that more women caregivers than men reported emotional stress and impaired physical health.
It would be universally beneficial to lessen the burdens on the caregivers and to increase quality of care and quality of life issues for the elders. To this end, Medical Automation Research Center (MARC), at the University of Virginia, has developed technological solutions for in-home monitoring of residents in order to provide quality of life indicators. The in-home monitoring system is composed of a suite of low-cost, non-invasive sensors (strictly no cameras or microphones), and a data logging and communications module, in addition to an integrated data management system, linked to the Internet. We have generated preliminary data from an activity monitor that logs the activities of the subjects onto a computer database.
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Using the appropriate data analysis tools, important observations can be made from the activity data generated by the monitored individual. These observations include: general health and activity levels, Activities of Daily Living (ADL), most Instrumental Activities of Daily Living (IADL), index of well-being, and a measure of the decline in ability over time. These observations may yield early indicators of the onset of a disease. Additionally, a sudden change of activity (or inactivity) can indicate an accident. Although the system is not meant as an emergency prompt system, the caregiver may receive alerts over the Internet or urgent notifications over the phone in case of such sudden accident indicating changes. Software tools can generate reports of health/ activity indicators and the overall well being of the individual. Moreover, the system will provide a confirmation of activity levels; thereby encouraging reality based decision-making. Feedback reports can be sent to monitored subjects, their designated informal caregiver and their health care provider. Feedback to the individual can encourage the individual to remain active. The content of the report may be tailored to the target recipient’s needs, and can present the information in a format understandable by an elder person unfamiliar with computers, via an appealing user interface. Whereas feedback to the informal caregiver (family or friend) will provide them with peace of mind if their loved ones are doing well, and will improve the social content in their interactions with their elders. Hence, the informal caregiver will have access to the health and well- being status of their elders without being intrusive, having to call or visit to get such information interrogatively.
Additionally, formal care providers will receive a report on the health of the monitored subjects that will help them evaluate these individuals better during the short routine check up visits.
It is anticipated that the use of this technology will result in:
Improved informal care effectiveness without increasing intrusion.
Reduced cost of informal care, which is particularly high for older adult populations.
Reduced burdens on the informal caregiver, and hence reduced stress and improved mental and physical health conditions.
Involving the care recipient in health promoting activities and decision-making.
An extended healthy, active and dignified life for the elders that can be widely accessible to the low-income strata of society.
Delayed admittance to specialized institutions, and hence a reduced cost of formal elder care.
Reduced formal care burdens, and hence improved formal care.
MARC Smart In-Home Monitoring System has the following unique characteristics:
Implemented in simple low-cost sensor technology, which makes it affordable to the lowest 30% of income earners.
Adaptively retrofits into existing home structures, with minimal impact, modification and cost.
The data-mining component yields unique health status reports that can be made available to the occupants, their medical advisors and their family members.
The system is customizable to the individual’s needs, as well as different cultural needs.
Click Here to visit our Smarthouse website and take a tour to see the data collected and displayed onlne.
Development of Survey Instruments to Guide the Design of Health Status
Monitoring Systems for the Elderly: Content Validity Evaluation
Majd Alwan, Beverely Turner, Steve Kell, Kim J. Penberthy, Wendy Cohn, and Robin Felder. The 2nd IEEE International Conference on Information & Communication Technologies: from Theory to Applications - ICTTA’06, April 24 - 28, 2006 in Damascus, Syria.
Psychosocial Impact of Monitoring Technology in Assisted Living: A Pilot Study
Majd Alwan, Jon Leachtenauer, Siddharth Dalal, David Mack, Steve Kell, Beverely Turner, Robin
Felder. The 2nd IEEE International Conference on Information & Communication Technologies: from Theory to Applications - ICTTA’06, April 24 - 28, 2006 in Damascus, Syria.
Psychosocial Impact of Passive Health Status Monitoring on Informal
Caregivers and Older Adults Living in Independent Senior Housing
Majd Alwan, Steve Kell, Beverely Turner, Siddharth Dalal, David Mack, and Robin Felder. The 2nd IEEE International Conference on Information & Communication Technologies: from Theory to Applications - ICTTA’06, April 24 - 28, 2006 in Damascus, Syria.
A Smart and Passive Floor-Vibration Based Fall Detector for Elderly
Majd Alwan, Prabhu Jude Rajendran, Steve Kell, David Mack, Siddharth Dalal, Matt Wolfe, Robin Felder. The 2nd IEEE International Conference on Information & Communication Technologies: from Theory to Applications - ICTTA’06, April 24 - 28, 2006 in Damascus, Syria.
Impact of Passive In-Home Health Status Monitoring Technology in Home Health: Outcome Pilot
Majd Alwan, David Mack, Siddharth Dalal, Steve Kell, Beverely Turner, Robin Felder. Proceedings of the Transdisciplinary Conference on Distributed Diagnosis and Home Healthcare (D2H2), 2 - 4 April 2006, Arlington, VA.
Impact of Monitoring Technology in Assisted Living: Outcome Pilot
Majd Alwan, Siddharth Dalal, David Mack, Steve Kell, Beverely Turner, Jon Leachtenauer, Robin Felder.
IEEE Transactions on Information Technology in Biomedicine. Jan 2006
IT’s Elder Care Intervention: Passive in-home monitoring systems can reduce the cost of care while improving elders’ quality of life.
Most Wired Magazine. November 2005.
Validation of Rule-Based Inference of Selected Independent ADLs
Majd Alwan, Jon Leachtenauer, Siddharth Dalal, Steve Kell, Beverely Turner, David Mack, Robin Felder.
Journal of Telemedicine and E-Health. Oct. 2005
A Rule-Based Approach to the Analysis of Elders’ Activity Data:
Detection of Health and Possible Emergency Conditions
Siddharth Dalal, Majd Alwan, Reza Seifrafi, Steve Kell, Donald Brown
AAAI Fall 2005 Symposium (EMBC). Sep. 2005.
VOA Pilot Outcome
Majd Alwan. March 2004.
In-Home Monitoring System and Objective ADL Assessment: Validation Study.
Majd Alwan, Steve Kell, Siddharth Dalal, Beverely Turner, David Mack and Robin Felder
International Conference on Independence, Aging and Disability, 2003.
Health Status Monitoring Through Analysis of Behavioral Patterns
Tracy Barger, Donald Brown, Majd Alwan. To Appear in Lecture Notes in Artificial Intelligence (LNCS/LNAI), Proceedings of the 8th congress of the Italian
Association for Artificial Intelligence (AI*IA) on Ambient Intelligence, Springer-Verlag, Pisa, Italy, September 2003.
MARC Smart Home receives honorable mention in the 2003 Innovative Housing Technology Awards (IHTA)
TecHome Builder Jan/Feb 2003.
Objective Remote Assessment of Activities of Daily Living (ADL)
Barger, Alwan, Kell, Turner, Wood, Naidu. CBI Steps to Success (2002)
MARC-ED: An Electronic Diary for Activity Data Collection in Smart Home Environment
Turner, Cohen, Reynolds, Kell, Alwan. CBI Steps to Success (2002)
Smart Houses Keep Eye on Elderly
TechTV, Oct. 14, 2002
Smart Sensors
Bazzirk Tech Ranch (Radio Interview with Steve), Sep. 23, 2002
Smart Tools for the Elderly
Technology Review, Aug. 12, 2002
Digital tools for age-smart housing
Architectural Record | Digital Architect, July 2002
