Eldercare applications for robotics technologies have interested researchers for some time now. They have monitored vital signs, aided with physical therapy, and helped seniors navigate through nursing homes. According to one University of Missouri professor, however, it is unclear which, if any, of these types of solutions will be widely used.
“There is a temptation to propose a robotic solution just because robots are cool,” says Marjorie Skubic, a professor of electrical and computer engineering at the University of Missouri in Columbia, Mo. “However, the key to making a successful product for the mass market is identifying a need and then proposing a solution that addresses that need.”
For this reason, Skubic is working with MU College of Engineering students to find practical solutions to mitigate risks for seniors. “The solution may not look like our current idea of a robot,” Skubic explains, “but may have some interesting robotic components.”
Mitigating Risk
One example of this work made headlines this month when the university announced that doctoral student Erik Stone was leading a project at an independent living community called TigerPlace, also in Columbia. Stone engineered the use of a Microsoft Kinect motion-sensing gaming camera to monitor the physical behavior and routine changes of TigerPlace residents.
The Kinect uses infrared light to create a depth image that produces data in the form of a silhouette. The data can be monitored for changes that could indicate an increased chance of falls or other behaviors associated with risk in elder populations.
“This type of needs-driven research and development might move robotics research into new directions,” Skubic says of Stone’s work. “I would like to see more interdisciplinary teams, including undergraduate and graduate students working on these problems. There are real challenges to be met, and we need the fresh young minds with their new ideas.”
Targeting Lifestyles
Skubic isn’t the only MU professor focusing on robotic and computer-engineered solutions for eldercare situations. Dr. Mihail Popescu is an assistant professor of medical informatics, health management. He, too, is working with students to develop risk-mitigating solutions for seniors.
Doctoral student Liang Liu, for example, in collaboration with Popescu, has developed a fall-detection system using Doppler radar. The system assigns “signatures” to body parts. Changes in the movement of these signatures during walking, bending, and other activities can help identify an increased risk of falls or injuries. “Falls are especially dangerous for older adults,” Liu says, “and if they don’t get help immediately, the chances of serious injury or death are increased.”
In the past, helping the elderly navigate their environment meant “instrumenting” them with “a variety of wearable sensors,” explains Popescu. “While this is a perfectly valid approach [to monitoring], we at MU started by asking the elderly what they would like. The conclusion … was clear: [the] elderly don’t want to wear sensors.”
This response led MU researchers toward “nonwearable solutions,” Popescu adds. “It departs from the robotics paradigm, where the robot is the center of the world.” The key term in the work of Popescu’s students is “lifestyle.” As the assistant professor explains, “If a medical device that targets lifestyle is accepted by consumers, it will likely have a great impact on our society.”
