Real-Time Location System to predict dementia

CAMBRIDGE, Sept. 8, 2011 â A recent study conducted at the University of South Florida employed Ubisenseâs real-time location system (RTLS) to track the movements of residents of two assisted living facilities (ALF). Using Ubisenseâs solution and fractal mathematics, the researchers discovered that persons with dementia demonstrated more random movement in their walks and this random component was a better predictor of dementia than the Folstein MiniâMental State Examination (MMSE), a primary tool used by clinicians to test for dementia.Leading the study was Dr. William Kearns, an associate professor in the Department of Rehabilitation and Mental Health Counselling at the University of South Florida. Dr. Kearns and his team tracked the daytime movements of 25 elder ALF residents, 14 of whom had been diagnosed with dementia. The elders agreed to wear the Ubisense Compact Tags secured by a wristband and be monitored for 30 days during waking hours. Ubisense sensors were installed in the common use areas of the ALF.The studyâs primary aim was to examine the relationship of dementia to path tortuosity (the number of changes in direction of successive movement paths) and to movement speed and path length variability. Ubisenseâs RTLS system tracked both changes in path direction and rate and duration of movement. The researchers found path tortuosity was greater in persons with dementia, and may be linked to impaired spatial memory required for successful navigation.âWe consider this to be a substantial finding and one that could potentially help us diagnose dementia earlier and enable us to provide better care for people demonstrating cognitive decline,â said Dr. Kearns. âPeoplesâ behavior is the best indicator of whatâs going on with them, and Ubisenseâs RTLS system is the best solution weâve found to provide the level of precise accuracy we need to validate our findings.â Dr Kearns has been studying people with dementia for seven years in order to better understand the relationship of movement changes to future cognitive decline and fall risk. His goal is to discover ways to allow older persons to remain in their homes longer and to ease caregiver burden. More than 35 million people live with dementia worldwide. Over the next 40 years that number is projected to hit 115 million.Dr. Kearns first attempted to use an RFID-based system for his studies but found it produced inaccurate location data. A colleague in the USF College of Engineering suggested he consider ultra-wideband (UWB) technology for more precise accuracy, and Dr. Kearns sought help from Ubisense.âThis is great validation of our support for academic partners,â said Adrian Jennings, vice president of technology for Ubisense. âItâs people like Dr. Kearns who develop important new applications for our location solutions, applications which would be difficult to research outside of academia. Weâre delighted to see the results of that openness, and proud to be a core element of Dr. Kearnsâ important work.âAs a result of their valuable research, the United States Patent Office recently awarded a patent to Dr. Kearns and his colleagues for the âHuman and Physical Asset Movement Pattern Analyzer,â which is an extension of their research using Ubisenseâs RTLS. The Pattern Analyzer, based on UWB technology, helps identify changes in older individuals in ALFs. It is equally applicable to the study of traumatic brain injury in veterans.For more information on Dr. Kearnsâ research, see:

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