[Image courtesy of MIT]
The device, called the Elderly Bodily Assistance Robot, or E-BAR, acts as a robotic set of handlebars that follows a user, providing support during movement and physical transitions. The robot can lift a person’s full body weight and is equipped with side airbags that inflate instantly to cushion a fall.
“Many older adults underestimate the risk of fall and refuse to use physical aids, which are cumbersome, while others overestimate the risk and may not exercise, leading to declining mobility,” said Harry Asada, the Ford Professor of Engineering at MIT. “Our design concept is to provide older adults having balance impairment with robotic handlebars for stabilizing their body. The handlebars go anywhere and provide support anytime, whenever they need.”
According to MIT, falls are the leading cause of injury among adults 65 and older. The researchers designed E-BAR to reduce that risk while preserving a sense of autonomy. Unlike other assistive technologies, E-BAR requires no harness or wearable devices and allows users to walk between the robot’s U-shaped handlebars or lean on them as needed.
In lab tests, the robot helped an older adult volunteer bend to pick up an item, reach overhead, and step over the edge of a bathtub. They were able to perform these actions without losing balance.
“Elderly people overwhelmingly do not like to wear harnesses or assistive devices,” said E-BAR designer Roberto Bolli, a graduate student in the MIT Department of Mechanical Engineering.
The system’s 220 lb. base uses omnidirectional wheels to maneuver easily through home spaces, and its articulated arms reconfigure to lift or support users naturally.
The robot is currently operated by remote control, but the team plans to automate its functions and streamline its size. Bolli and Asada will present the design at the IEEE Conference on Robotics and Automation later this month.
While E-BAR does not yet include predictive fall algorithms, Asada’s lab is developing machine learning models in parallel that could assess a person’s fall risk in real time and trigger responses accordingly.
“I think eldercare is the next great challenge,” said Bolli. “All the demographic trends point to a shortage of caregivers, a surplus of elderly persons, and a strong desire for elderly persons to age in place. We see it as an unexplored frontier in America, but also an intrinsically interesting challenge for robotics.”
The work is funded in part by the National Robotics Initiative and the National Science Foundation.
