The US Center for Disease Control and Prevention has revealed that Senior Americans aged 65 and more die mainly because of injuries from falls. Researchers from Virginia Tech, with help from a $1.2 million funding from the NSF Smart Health and Wellbeing Program have developed a handy fall prediction monitoring device, which would help to detect fall risks early and also help in diagnosing and treating the patient before the fall occurs.
Karen Roberto, professor of human development and director of the Center for Gerontology and the Institute for Society Culture and Environment; Thurmon Lockhart, an associate professor with the Department of Industrial and Systems Engineering; and Dong Ha, professor of electrical and computer engineering, all at Virginia Tech, are working on a project to stem elderly falls. Credit: Virginia Tech Photo
According to Thurmon Lockhart, an Associate Professor at Virginia Tech, the users would fix the sensor on their clothes or on their ankles for measuring tiny changes in mobility, posture and gait, which are indicators of future falls. The research project was carried out by Thurman along with a host of other researchers from Virginia Tech and the University of Virginia such as Karen Roberto, John Lach, to name a few.
Roberto has revealed that their attention was on preventative measures for reducing accidents from falls. According to Lockhart, the amount of money spent by the country on health care was dramatically high and growing every day. In the past a prototype of the sensor had already been tested, and now they were planning to develop the Remote Observation Operating Platform (ROOP) alert monitoring system, which would combine posture and gait analysis along with gerontology and wireless communication.
The diminutive sized sensor when worn on minimally invasive areas of the body would send data continuously to the ROOP-Alert system station located in the nurse’s office for recognizing the various symptoms and signs of falling. The testing would first be carried out at a Radford Nursing Home. software and algorithms along with low power radio development would be focused on by Ha and Lockhart, while Lach would concentrate on the hardware side of the equipment such as batteries.
Source: http://www.ise.vt.edu/main/index.php