Fall prevention sign


Wearable Airbag-sensor Technology Could Help Predict Falls & Cushion Impact


Worldwide, more than 37 million hospitalizations due to fall injuries occur each year, leading to $40 billion in medical expenses. Falls are particularly common in groups at greater risk, such as people over 65 and the millions who have injuries or diseases that affect the brain, nerves and muscles — including stroke and Parkinson’s disease (PD).

Although many fall-prevention steps are taken through traditional rehabilitation (including physical therapy), preventing all falls is impossible. Further, in adults with stroke or PD, the risk of falling can be many times greater in comparison with healthy peers of the same age. Despite robust research and prevention strategies, people continue to fall and experience debilitating injuries as a result.

Clearly, a second line of defense is called for. The ability to predict a fall quickly and accurately is key. Simultaneously, tying prediction to protection can help minimize the risk of fall-related injury.

Scientists at Shirley Ryan AbilityLab are leading the charge to develop better fall-detection models and advance fall-mitigation technologies, such as wearable airbags for individuals at high-risk of falling. Their hope: that use of such devices could reduce risk of fractures, injuries and fear of falling, thereby improving overall health and quality of life in at-risk populations.

An Ever-present Threat


There are many reasons that fall risk is higher in people following a stroke or PD diagnosis. These conditions can affect balance, strength, vision and the ability to move or control movement. Use of medication can also increase risk of falling. In addition, once someone falls, it is more likely that he or she will fall again.

Complications from falls greatly increase the chance of long-term illness and debility. Among fall-related injuries, hip fracture is a common complication that often leads to life-changing and life-threatening complications. Although hip pads have long been available to help prevent injury, their bulky and conspicuous nature have prevented widespread adoption.

Accelerating Next-gen Rehabilitation Technology


With the goal of keeping people with stroke or PD out of the hospital for fall-related complications, it makes sense to combine fall prediction and protection. Doing so is the goal of scientists in Shirley Ryan AbilityLab’s Max Näder Center for Rehabilitation Technologies and Outcomes Research, led by Arun Jayaraman, PT, PhD. The Center is a unique, one-stop-shop for industry and academic groups developing next-generation rehabilitation technologies.

The Center’s top scientists, engineers and clinicians offer research partners a wide range of expertise, e.g., product evaluation, clinical trial implementation, support in achieving regulatory clearance, Medicare and Medicaid reimbursement, as well as product commercialization.

Meanwhile, the advantage for Shirley Ryan AbilityLab’s patients is clear: the collaboration helps potentially game-changing investigational technologies get to market faster, and patients gain access to those technologies for clinical or home use, years — even decades — sooner than otherwise possible.

Immediate-impact Research Collaboration


“I call what we do ‘immediate-impact research,’” Dr. Jayaraman said. “We can’t build all the devices, and we can’t design all the clinical trials — but we can leverage our organization’s expertise in rehabilitation research, applied to our populations, for testing new technologies, quickly."

For Kyle Embry, PhD, team scientist, this work is personal. “When I was in high school, my grandmother fell and then passed away from complications a year later,” he said.

The Center’s differentiated approach has resulted in Shirley Ryan AbilityLab’s collaboration with industry leaders.

One such leader is Wolk, a Dutch company that has developed a wearable airbag system designed to detect and lessen the impact of falls. The device resembles comfortable bike shorts equipped with three tiny motion sensors — one on each hip and one on the lower spine. The device is lightweight and can be worn discreetly under normal clothing.

Scientists at Shirley Ryan AbilityLab are developing algorithms for the technology to accurately detect falls for people with a history of stroke or PD. Together the “airbag devices,” plus fall-detection algorithms, form a wearable protection system.

Shirley Ryan AbilityLab scientists are refining the system to make it more robust, more sensitive and population-specific. “Because the Wolk design was developed from data drawn only from a general, aging population, we are focused on optimizing effectiveness specifically in two of our populations with neurologic impairments,” said Dr. Jayaraman. “Our algorithms are highly specific and know the difference between an actual fall and other everyday actions, such as bending down to pet a dog or tie a shoelace.”

Refining Technology for Better Outcomes


The airbag device uses a series of motion sensors that are working continuously. The sensors send data to a fall-detection algorithm, which looks for the physiological signs of a fall and activates a small, hip-worn airbag if needed. The airbag inflates with carbon dioxide (CO2) gas released from a wearable cartridge, hopefully reducing the impact force on the hip during a fall.

Drs. Embry and Jayaraman are using machine-learning techniques to fine-tune the algorithm.

“Our fall-detection algorithm tries to determine if the sensor data we are collecting indicates whether the person is falling,” says Dr. Embry. “If it is confident that the fall is occurring, it will deploy airbags — in a fraction of a second — from the correct side of the body.”

From Research & Development to Everyday Clinical Impact


Currently, the system is being tested by 14 patients with stroke or PD from around the Chicagoland area. They are the first people ever to use the device in their day-to-day activities, and the sensors are providing data on safety and efficacy.

Shirley Ryan AbilityLab researchers will contact participants every two weeks to collect data on falls and compliance. During in-lab visits, participants will complete surveys and assessments to determine if they are more active, have increased functional mobility and are experiencing improved quality of life. Ultimately, researchers plan to publish their findings and ensure that knowledge is translated into the clinical domain.

“The goal is to prevent hip fractures in high-risk populations,” says Dr. Embry. “We’re hopeful that our contributions to this research will expedite the amount of time it takes for this technology to reach patients — and will lead to better outcomes for the millions of people who fall each year.

As a next step, the research team hopes to secure federal and foundation grants to support larger deployments of this technology to more patients for everyday use.

For more information:

Botonis, O. K., Harari, Y., Embry, K. R., Mummidisetty, C. K., Riopelle, D., Giffhorn, M., ... & Jayaraman, A. (2022). Wearable airbag technology and machine learned models to mitigate falls after stroke. Journal of neuroengineering and rehabilitation19(1), 60.


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