Recognition Technology for Aging in Place
The continuous assessment of physical and cognitive function is a key indicator of initial decline in health and functional ability. Identifying and assessing problems while they are still small can provide a window of opportunity for interventions that will alleviate the problem areas before they become catastrophic. In this talk, Dr. Skubic will describe ongoing interdisciplinary work to investigate the use of sensor technology and automated reasoning to provide early identification of illness and functional decline. The integrated sensor network under development includes motion detectors, a bed sensor that captures pulse, respiration and restlessness in bed, a stove temperature sensor, and new fall detectors using radar and acoustic sensing. In addition, a video sensor network using silhouette imagery for privacy is being developed to capture gait parameters such as walking speed, step length, and body sway for use in assessing fall risk. The network is being tested in TigerPlace, an aging-in-place facility designed to help residents manage illness and impairments and stay as healthy and independent as possible.
Dr. Marjorie Skubic received her Ph.D. in Computer Science from Texas A&M University. She is currently a Professor in ECE with a joint appointment in Computer Science. Dr. Skubic has received funding from the NSF, NIH, NGA, the U.S. Administration on Aging, the Naval Research Lab, and the U.S. Army. In addition to her academic experience, she has spent 14 years working in industry on real-time applications such as data acquisition and automation. Her current research interests include sensory perception, computational intelligence, spatial referencing interfaces, human-robot interaction, and sensor networks for eldercare. In 2006, Dr. Skubic established the Center for Eldercare and Rehabilitation Technology and serves as the Director for this interdisciplinary center.