New Kind Of Sensor System Is Capable Of Predicting Fall Of Senior Citizens 3 Weeks Before It Takes Place

predict fall of seniors

Figure 1: Sensor predicts fall of senior citizens 3 weeks before something happens

The only people who face most dire consequences of small casual falls are either sick or in their old age. These are the most vulnerable states that need proper care and attention from care takers and givers. In case, of falls the old people many a times face head injuries, broken bones, clots, and other deadly results that result in their untimely demise many a times. But a team of researchers working in the Sinclair School of Nursing along with the College of Engineering in the University of Missouri, recently found a solution to it. The sensors that are capable of measuring in-home gaits and length of strides can easily predict when a person is expected to fall in near future, to be specific in a period of three weeks.

Marjorie Skubic, the MU center for Eldercare and Rehabilitation Technology and a professor of computer engineering and electrical engineering, likes to explain, “We have developed a non-wearable sensor system that can measure walking patterns in the home, including gait speed and stride length. Assessment of these functions through the use of sensor technology is improving coordinated health care for older adults” In order to predict the likeliness of fall the sensor system mainly utilizes the data collected from the sensor system at a new kind of ageing-in-place retirement home, TigerPlace located in Columbia. The system sends images and alert emails to the caring staff whenever any irregularity in motion is detected. The information can be vital in helping nurses in checking the functional decline and offering proper treatment that can prevent the falls.

A Professor of Nursing at the Curators, Marilyn Rantz feels, “Aging should not mean that an adult suddenly loses his or her independence. However, for many older adults the risk of falling impact how long seniors can remain independent. Being able to predict that a person is at risk of falling will allow caretakers to intervene with the necessary care to help seniors remain independent as long as possible”.

The results given by the sensor system data discovered that a decline of five centimeters in the gait speed of an associated person increases the probability of their falling by 86.3 percent in next three weeks.The team working on it also found that that the decreasing stride length was closely associated with a 50.6 percent probability of falling in upcoming 21 days.