What the Science Actually Showed
Falls are not random. For older adults, they follow patterns rooted in gait degradation — and that means they can be studied, modeled, and interrupted before they happen.
Building the Evidence Base
The SMILING project drew on longitudinal gait analysis across multiple clinical sites, combining biomechanical measurements with neurological assessments to identify the earliest markers of fall risk. Rather than relying on self-reported symptoms, the team developed objective sensor protocols that captured subtle changes in stride length, cadence, and postural sway over time.
Key Research Outcomes
- Quantified the correlation between reduced hip extension and recurrent fall events in adults over 70
- Validated a mechatronic exoskeleton framework for assisted gait retraining in clinical and home settings
- Established adaptive feedback algorithms that adjust support levels in real time based on user effort
- Demonstrated measurable improvement in balance confidence after structured training sessions
Interested in the full methodology or clinical trial data? The project publications offer a detailed account of every phase.
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