MIT Engineers Build Robot That Can Catch, Lift Seniors If They Fall

CAMBRIDGE, Mass. — Over 11,000 Americans turn 65 each day, and with each passing year comes more risk for one of the most dangerous threats of aging: falls. But have no fear! Researchers from the Massachusetts Institute of Technology (MIT) have designed a new robot, aptly named E-BAR (Elderly Bodily Assistance Robot), that can lift a person from the floor, help with daily movements, and catch someone during a fall, all without requiring them to wear any special harness or device.

Ninety-two percent of elderly Americans strongly prefer to age in their homes rather than move to assisted living facilities, but falls remain the leading cause of injury for those over 65. In fact, approximately one in four elderly Americans—nearly 14 million people—falls each year.

This research, set to be presented at the IEEE Conference on Robotics and Automation (ICRA), provides new safety technology for seniors who are afraid of falling but don’t want to be put in a nursing home or assisted living facility.

“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,” says study author Harry Asada from MIT, in a statement.

Most elderly individuals resist wearing restrictive devices despite needing assistance, and switching between different assistive technologies can be hazardous for older adults trying to manage independently.

The Fall Prevention Robot

What separates E-BAR from existing eldercare robots is its unique combination of features in a single system. While other robots might help with standing or walking or provide fall detection, E-BAR does it all with a surprisingly slim profile—just 38 centimeters at its narrowest point. This allows it to navigate through typical home doorways and around furniture.

The robot functions like an invisible safety net positioned behind the user. Its U-shaped fork can provide support under the arms or at the forearms, enabling activities that many elderly people avoid due to fear of falling, such as bending to pick up objects or getting in and out of bathtubs.

When the team tested the robot with elderly participants and caregivers, they found that many older adults have enough muscle strength for daily activities but lack confidence in their balance. E-BAR targets exactly this population, the approximately 24% of Americans over 65 who have significant muscle strength but require assistive devices, and the 28% of those over 75 who show increased fall risk in clinical assessments.

Making Independent Living Safer

Unlike most support robots that require the user to stand within the robot’s base footprint, E-BAR can extend its support arm across gaps like bathtub edges while maintaining stability. This was achieved through computational optimization that balanced competing priorities like footprint size, reach distance, and stability.

To create the lifting mechanism, the MIT team developed an innovative 18-bar linkage system that follows the natural trajectory of human movement when transitioning from sitting to standing. This mechanism provides maximum mechanical advantage at key points where users need the most help, mimicking how a caregiver might assist someone.

The E-BAR includes four rapidly inflating airbags that can deploy in less than 250 milliseconds to catch someone during a fall. The system monitors for balance issues and can predict a fall before descent begins, giving the airbags enough time to inflate and safely cushion the user.

Even though falls happen quickly, there’s a brief but crucial window of opportunity between initial imbalance and the actual fall that allows the system to deploy its protective measures.

The airbags were specifically designed with elderly skin in mind. They use neoprene foam coverings to provide high friction with clothing while distributing pressure over a large enough area to prevent bruising.

User-Centered Design for Everyday Challenges

For mobility, the robot uses an omnidirectional drive system with four independently controlled wheels that can rotate in any direction. When the robot’s wheels are positioned in an X shape, it stays steady on its own, even when pushed from the side. In fact, it can handle more than twice the force experts say it would normally need to support during everyday use, based on consultations with healthcare professionals.

The robot’s development followed a user-centered approach from the beginning, with input from nurses, care professionals, and elderly individuals at multiple stages. This resulted in practical features like padding on all potential contact points to prevent bruising elderly skin and handlebars allowing users to grip the support in multiple orientations.

“Eldercare conditions can change every few weeks or months,” says Asada. “We’d like to provide continuous and seamless support as a person’s disability or mobility changes with age.”

In testing scenarios, E-BAR successfully assisted users with challenging activities like getting into and out of bathtubs, bending to reach objects, transitions from sitting to standing, and walking. Adult participants reported that tasks which previously averaged a difficulty rating of 3.17 out of 5 dropped to just 1.83 when using the robot.

“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,” says study author Roberto Bolli from MIT.

Vacancy rates in the U.S. eldercare workforce are already between 20% and 25%. With nursing home costs averaging over $108,000 annually, technology that delays or prevents institutional care could provide significant economic benefits while respecting elderly individuals’ preferences for independence.