Gait sensors predict falls, allowing preventive intervention

University of Missouri’s Marjorie Skubic has used sensors to measure gait speed and stride length, to predict falls.  The goals is to use wearables and smart home technology to preserve independence and allow seniors to age in place.

Data was collected at an independent-living style retirement residence. Images and nurse alert emails were generated when irregular motion was detected. The researchers determined that a gait speed decline of 5 centimeters per second was associated with an 86.3 percent probability of falling within three weeks.  A shortened stride length was associated with a 50.6 percent probability of falling within three weeks.


Wearable Tech + Digital Health + NeuroTech Silicon Valley – February 7-8 @ Stanford University – Featuring:   Vinod Khosla – Tom Insel – Zhenan Bao – Phillip Alvelda – Nathan Intrator – John Rogers – Mary Lou Jepsen – Vivek Wadhwa – Miguel Nicolelis


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