Online Program

335811
Ambient Sensor Monitoring to Enable Aging in Place for Older Adults


Wednesday, November 4, 2015

Ali Yalcin, Ph.D., Department of Industrial and Management Systems Engineering, University of South Florida, Tampa, FL
Ngozichukwuka Agu, MBBS, MPH, Department of Community and Family Health, College of Public Health, University of South Florida, Tampa, FL
Garrick Aden-Buie, BA, BS, Department of Industrial and Management Systems Engineering, University of South Florida, Tampa, FL
Julie Hammett, BS, MS, Department of Industrial and Management Systems Engineering, University of South Florida, Tampa
Efe Yetisener, Department of Industrial and Management Systems Engineering, University of South Florida, Tampa
Chad Radwan, MA Applied Anthropology, Department of Community and Family Health, University of South Florida, College of Public Health, Tampa, FL
Victoria Salow, MPH, Department of Community and Family Health, University of South Florida, College of Public Health
Carla L. VandeWeerd, PhD, Department of Industrial and Management Systems Engineering, University of South Florida, Tampa, FL
The number of adults aged 65 and older in the US is predicted to double by 2040. Early detection of onset or progression of chronic conditions among this growing population can prevent costly health complications, decrease caregiver burden, and increase seniors’ independence. AlwaysNear is a 24/7 in-home ambient sensor system that monitors 13 activities of daily living (ADLs) (e.g. toileting, mobility, sleep) and generates notifications when ADLs deviate significantly from baseline levels.  Changes in ADLs can indicate chronic conditions including diabetes, depression, and sensory impairment.  

The objectives of this study were to evaluate AlwaysNear’s ability to detect 13 target ADLs and to generate timely notifications when ADLs deviate from baseline levels. To validate the sensors’ detection capability and notification system, eight contact sensors and one motion sensor were embedded into a Living Lab and 12 notifications (e.g. excess time in bed; too few refrigerator openings) were programmed into the system. Target activities were performed by research assistants and all activities, excluding toileting, were accurately detected by the sensors. Most activity notifications (ADLs in excess of baseline) were reliably generated, however, inactivity notifications (ADLs below baseline) did not generate reliably.   

Recommended system improvements included more sensitive motion sensors and more reliable inactivity notifications. The sensors’ detection capabilities, however, already offer a promising mechanism to facilitate seniors “aging in place”.  Further, AlwaysNear has the potential to integrate with electronic medical records and homecare services to enhance the current prevention capabilities of geriatric medical practitioners and improve the health and safety of seniors.

Learning Areas:

Chronic disease management and prevention

Learning Objectives:
Describe how ambient sensor technology can be used to detect changes in activities of daily living. Identify activities of daily living that indicate the onset or progression of chronic illnesses among aging adults and can be monitored using ambient sensor technology.

Keyword(s): Aging, Technology

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a PhD student in the Department of Community and Family Health with a medical background. I am involved in research that aims to improve the quality of life of older adults.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.