A network of wireless sensors engineered to detect falls and developed by University of Utah electrical engineers may eliminate the need for older adults to wear an alert system, according to a university news release. The release notes that Brad Mager, graduate student in electrical and computer engineering, and Neal Patwari, PhD, designed the fall-detection system using a two-level array of radio-frequency sensors placed around the perimeter of a room at two heights that correspond to an individual standing or lying down.
The system could potentially be linked to a service that would summon emergency help for older adults without requiring them to wear a monitoring device, engineers say.
Patwari, senior author of the study, associate professor of electrical and computer engineering at the University of Utah, emphasizes the system’s promise in light of the expansion of aging-in-place. “Ideally, the environment itself would be able to detect a fall and send an alert to a caregiver. What’s remarkable about our system is that a person doesn’t need to remember to wear the device,” Patwari says.
The engineers report that during transmission from each sensor in the array to another, any individual standing or falling inside the network alters the path of signals sent between each pair of sensors. The system is engineered to use radio tomography to generate an image showing the approximate location of an individual in the room within a resolution of about 6 inches. This approach uses the one-dimensional link measurements from the sensor network to build a three-dimensional image, engineers say.
The university adds that the team hopes to develop the proof-of-concept technology into a commercial product through Patwari’s Utah-based start-up company, Xandem Technology.
Mager, first study author, explains that, “With this detection system, a person’s location in a room or building can be pinpointed with high accuracy, eliminating the need to wear a device,” Mager says.
The university adds that the system is also programmed to detect whether a dangerous fall has taken place or if the individual is simply lying down on the floor. In order to determine a time threshold for accurately detecting a fall, the researchers reportedly conducted a series of experiments to measure the amount of time that elapsed when an individual fell, sat down, or laid down on the ground. This information in turn was fed back into algorithms used to determine whether the event was the result of a fall or a benign activity.
[Photo Credit: Dan Hixson, University of Utah]
[Source: University of Utah]
