Every step tells a story. And for millions of older adults, that story can include a hidden risk of falling, one that often goes undetected until it's too late.
A comprehensive review entitled “Fifteen Years of Wireless Sensors for Balance Assessment in Neurological Disorders,” published in Sensors, analyzes 15 years of innovation in wireless sensors for balance assessment across neurological conditions. The findings are clear: while wearable devices have opened powerful new doors in balance and gait analysis, even they have limitations, especially when it comes to detecting fall risk in real life.
Let’s break it down.
According to the study, a history of falls remains the single strongest predictor of future falls, but clinical tools struggle to catch issues early enough:
“To date, a history of falls is the strongest predictor of future falls… thus underscoring the need for predictive measures to determine early preventive interventions.”
And yet, most clinical assessments fail to catch subtle warning signs:
“Clinical assessment is subjective and is not sensitive enough to identify early balance control dysfunction… Conversely, traditional laboratory evaluation… does not always reflect real-life situations.”
In other words, even the most experienced clinicians may be missing early red flags simply because current tools don’t capture what’s happening in real life.
Wearables Help (But Don’t Go Far Enough)
The Sensors review details how inertial measurement units (IMUs), EMG sensors, and instrumented insoles have made balance assessments more objective. These tools have shown great promise across Alzheimer’s, Parkinson’s, multiple sclerosis, and more.
But there’s a catch: they depend on extra equipment, specialized setup, and controlled environments:
“These techniques are generally expensive, encumbering, and also require supervised settings… precluding their use for long-term monitoring in daily life situations.”
And that’s where the next evolution comes in.
OneStep eliminates the need for wearables altogether.
Using just a smartphone in the patient’s pocket, OneStep analyzes gait in seconds -and delivers a clear, clinically validated Fall Risk Assessment (FRA) that identifies who is at risk, why, and what to do next.
No wearables. No calibration.
OneStep has taken gait analysis out of the lab and into real life.
What sets OneStep apart?
In fact, OneStep’s FRA has been shown to detect subtle movement changes that might otherwise be missed, helping clinicians intervene earlier and prevent avoidable injuries. And we have the research to prove it. We recently analyzed data from 671 patients across two skilled nursing facilities with significantly different baseline fall rates. Despite these differences, the FRA system reliably stratified patients by relative fall risk within each facility. In comparison, individual metrics such as TUG time and gait velocity - while commonly used - showed reduced predictive accuracy, particularly in higher-risk environments. Time-to-event analysis reinforced the FRA system's ability to anticipate both the likelihood and timing of future falls.
Want to Go Deeper? 👉 Download the OneStep Fall Risk Assessment Research Paper
Explore the methodology, validation, and outcomes behind our smartphone-based fall risk detection.
The Sensors review celebrates the impact of wearable sensors in bringing objectivity to balance assessments. But as the paper itself notes, the next step is to remove friction and bring that objectivity into daily life.
OneStep makes that leap.
No hardware. No hassle. Just smarter insights, earlier action, and better outcomes.
Because the time to treat a fall… is before it happens.
We are how we move. And OneStep is how we can watch and listen.