Catch Me When I Fall

Catch Me When I Fall

According to the World Health Organisation, falls are the second leading cause of accidental or unintentional injury deaths worldwide, second only to traffic incidents. An estimated 646,000 individuals die from falls each year, with elderly and motor-impaired at the most risk. Even if a fall isn’t fatal, approximately 37 million such incidents annually are serious enough to require hospitalization, pushing global public health costs into the billions.

Education, training, and the creation of safer environments are all proven strategies to help mitigate the risks of injury and death, but what if technology could step in and provide new solutions to prevent fall-related fatalities?

Fulbright Scholar Michael Raitor’s research into biomechanics and haptic feedback technology could represent the greatest breakthrough in fall-prevention since the invention of the handrail. He is currently in Australia, capturing data on walking and movement patterns for clinical detection of abnormality, as well as potential use in ‘wearable’ fall prevention devices.

Michael soldering the electronic circuit that powers his concept device

“What we’ve learned so far from fall research is that we can model falls that we’ve observed in labs pretty well, but we know that falls simulated in a lab environment don’t accurately represent falls that occur in real life situations. So one of the areas of research that I’m interested in is gathering real-world information on ‘gait’ that we can use to identify abnormal patterns that may increase fall risk, and mitigate these risks through intervention, whether that be via physical therapy or an assistive device. Additionally, if a fall does occur while wearing the system, we could alert caretakers or first responders of the fall so the user gets help as soon as possible.

“We are also looking into targeting specific types of falls. There are many different causes for falls – you can fall by misstepping, tripping, or simply leaning to far to one side– and each may require a different approach to solve.”

Michael researches natural walking patterns and gait to create algorithms that can calculate fall probability

Michael is particularly interested in a promising new technology developed by Associate Professor Stephen Redmond at the University of New South Wales’ Biomedical Systems Laboratory.

“[A/Prof Redmond] is working on a ‘slip sensor’ that can determine how likely something is to slip. I’m looking at adapting this research into a shoe that can detect when someone wearing it is about to slip, and intervene in one of two ways: one would be subconscious, by actually augmenting their perceptual abilities, and the second would be a conscious vibration, through a cellphone or smartwatch.

“With the conscious approach, the implementation of a haptic feedback system would be less complex, however it’s not ideal – while the physical vibration may be useful to notify the wearer that they are about to fall, the distraction caused by this sudden sensation may in fact cause them to fall.

“The subconscious approach would involve stimulating the foot in such a way that the wearer would be better able to instinctively detect if they are about to slip, effectively augmenting their natural ability to prevent a fall from occurring.”

Scientia Professor Nigel Lovell, co-director of the Biomedical Systems Laboratory, has valued Michael’s contribution to their work.

“Michael has been an outstanding addition to our research group at UNSW.

“We are researching how to better characterise gait and movement. Using such measures we will be able to design wearable devices that interpret movements and, for example, automatically raise an alarm when a frail older person has fallen and failed to rise.

“Michael has contributed greatly to the analytic approaches and algorithms for this movement characterisation. He has embraced the Australian culture and is a superb ambassador for the Fulbright Program.”

Michael’s device in testing

One of the most amazing things about Michael’s story is that he has accomplished all of this research despite having a vision impairment of his own. Michael has Stargardt disease, a degenerative retinal condition symptomatically similar to macular degeneration.

This hasn’t held Michael back, however, and in fact has been one of his motivations for ensuring that new fall prevention technology is effective, and accessible.

“One thing that I’ve come across often, especially if I’m walking home in the dark, is that a lot of times I’ll stumble or catch myself just because of the lack of visual acuity, or uneven pavement.

“Through experiences such as this, it very quickly became apparent to me that in situations where you don’t have the visual cues you’re used to, falling becomes much more of a problem and you rely on other resources such as a relatively strong sense of balance in my case. The underlying causes of falls can vary widely among users and it’s important to create a robust solution that can be used to help as many patient populations as possible.Michael Raitor

“This realisation that falls aren’t isolated to the elderly, motor impaired, or distracted Twitter users was definitely a motivating factor to my current work.”

Until new technology is commercialised, falls will continue to be a serious public health risk, however thanks to the work of researchers such as Michael and Prof. Lovell’s team at UNSW, the testing and perfecting of these devices, as well as our understanding of human movement, will continue to improve in leaps and bounds.