Researchers at University of Virginia are developing wireless body sensors that monitor gait, a development that will reduce fall risk in elderly.
A new consortium of researchers from U.Va.'s School of Engineering, School of Medicine and Department of Psychology, in partnership with the U.Va. Institute on Aging's Translational Research Consortium and AFrame Digital, Inc., a health monitoring and medical alert products company, will soon be providing the wearable sensors to residents of some area long-term care facilities.
The group will use continuous data from these "living laboratories" to test and refine the technology.
"We are moving research from the lab to a living environment," said Regina Carlson, director of development for the Institute on Aging.
"Ultimately, we will gain better research data in these settings," the expert added.
Falls are the leading cause of injury death among people age 65 and older, according to research compiled by the Centers for Disease Control and Prevention. They are also the major cause of non-fatal injury and hospitalizations for trauma.
The tool being developed at U.Va. will aid in the identification of gait problems that may result in falls. By wirelessly connecting to a network set up by AFrame Digital, the sensors will provide researchers with real-time data on the nursing home residents' gaits.
Using this information, the researchers are working to commercialize a product that will eventually allow geriatricians to accurately assess gait problems and provide the proper interventions, such as a walker, before a fall happens.
This type of sensor technology is also a key component for transitioning to more health care being delivered in patients' homes.
John Lach, an associate professor in the Charles L. Brown Department of Electrical and Computer Engineering, has been researching and developing wireless body sensors for the past five years. In this application, the sensors can be worn like a wristwatch. Using parameters determined in a gait laboratory directed by D. Casey Kerrigan, a professor in the School of Medicine's Department of Physical Medicine and Rehabilitation, Lach has developed sensors that can quantitatively measure the walking patterns that are likely to lead to falls.
Lach's sensors, now about the size of a digital watch face, can measure and transmit data on a wide range of human motion, including linear acceleration, or how fast patients move in a straight path, and rotational rate, which together provide six degrees of freedom motion capture.