MIT engineers develop robot to support ageing population
As the median age of the United States population reached 38.9 – nearly ten years older than it was in 1980 – the country faces a growing demographic shift. By 2050, the number of adults over 65 is expected to rise from 58 million to 82 million, intensifying the challenges of eldercare amid shrinking care worker numbers, increasing healthcare costs, and changing family dynamics.
In response, researchers at the Massachusetts Institute of Technology (MIT) have developed a mobile robotic assistant designed to help older adults move safely and independently at home. Named the Elderly Bodily Assistance Robot, or E-BAR, the system aims to provide physical support and prevent falls – the leading cause of injury among people aged 65 and above.
The robot functions as a pair of robotic handlebars that follows a user from behind. It can provide full bodyweight support, assist with transitions between sitting and standing, and automatically deploy side airbags to catch a person in the event of 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, Ford Professor of Engineering at MIT.
“Our design concept is to provide older adults having balance impairment with robotic handlebars for stabilising their body. The handlebars go anywhere and provide support anytime, whenever they need.”
The current version of E-BAR is operated via remote control, but the MIT team is developing future iterations with autonomous capabilities. They are also working to make the system more compact and better suited to domestic spaces.
“I think eldercare is the next great challenge,” said E-BAR designer Roberto Bolli, a graduate student in MIT’s Department of Mechanical Engineering.
“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.”
Unlike other systems that use wearable gear or rigid support frames, E-BAR was designed without a harness. Instead, it provides unintrusive support with a U-shaped pair of handlebars that users can lean against when necessary. Each arm contains airbags made from a soft, grippable material that rapidly inflates in the event of a fall – a mechanism the team believes is a first for robotic eldercare without requiring wearable components.
“Elderly people overwhelmingly do not like to wear harnesses or assistive devices,” said Bolli.
“The idea behind the E-BAR structure is, it provides body weight support, active assistance with gait, and fall catching while also being completely unobstructed in the front. You can just get out anytime.”
The robot’s base, weighing approximately 220 pounds, has been engineered for stability and includes omnidirectional wheels, enabling it to move in any direction without needing to pivot – useful for navigating tight home environments. Its articulated body includes 18 interconnected linkages, designed to mimic natural movement as it lifts a person from a chair or provides support during walking.
During lab testing, an older adult volunteer used E-BAR to perform household tasks such as picking up objects, reaching shelves, and stepping over a bathtub ledge. The robot successfully assisted in all scenarios, offering support without impeding natural movement.
“Seeing the technology used in real-life scenarios is really exciting,” said Bolli.
The E-BAR prototype currently lacks fall-prediction capabilities, but related work in Asada’s lab, led by graduate student Emily Kamienski, is exploring machine learning algorithms to assess real-time fall risk and respond accordingly.
Asada envisions a suite of robotic solutions tailored to different stages of ageing.
“Eldercare conditions can change every few weeks or months,” he said. “We’d like to provide continuous and seamless support as a person’s disability or mobility changes with age.”
The research was supported by the National Robotics Initiative and the National Science Foundation.