But what if there was a measurable difference between a good step and a bad step? What if the quality of your gait could reveal more serious health issues?
Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), led by Professor Dina Katabi, think there is a difference, and they can measure it with a new wall-hanging device that reads wireless signals bouncing off your body as you walk around your house.
The CSAIL team announced their findings on Monday and will present their work this month at ACM’s CHI Conference on Human Factors in Computing Systems in Colorado.
WiGait is the name of the white, painting-sized device, which emits a tiny wireless signal (with less radiation than your garden-variety cellphone). It’s not intended to replace your Fitbit. Instead, it augments the information collected on your smartphone with details about how you walk or, as doctors refer to it, your “gait velocity,” or your walking pace in everyday life.
Most fitness measurement devices use precise accelerators to measure movement, but they have to guess at speed by indexing that pace with a GPS position. Indoors, there’s no way to measure distance covered. Speed and gait measurement becomes virtually impossible.
But WiGait can measure speed and stride-length and how it changes over time to assess changes in health. That information is represented on a companion app.
The system, which can be set up to track movement throughout the home (one unit might cover a small, one-bedroom apartment), also uses intelligence to identify the difference between walking and other actions like cleaning and sitting and reading.
Researchers claim it’s between 95%-to-99% accurate when measuring stride length.
As for privacy concerns, there’s no camera on WiGait. Walkers are represented as a dot on the screen.
Lead author and PhD student Chen-Yu Hsu told me that, initially, the researchers thought this technology could be used to very accurately identify someone’s location in a home. The realization that it could be used to track motion and health came later, “when we talked to doctors about how gait speed is a very important metric for geriatric medicine.”
Identifying changes in someone’s strides (think shorter steps) could help researchers better understand diseases like Parkinson’s, which can be characterized by gradual differences in gait.
During the four-to-five months of field study with the devices, the team made some important discoveries. In one instance, researchers detected that a test subject was getting up and pacing in the middle of the night. “Turns out that person had some issue with anxiety,” said Hsu.
Next step for Katabi’s team is to test WiGait on patients with Parkinson’s, Alzheimer’s, and Multiple Sclerosis.
The MIT CSAIL team hopes to integrate WiGait into Emerald, an in-home fall-monitoring system the team unveiled in 2015.
I asked Hsu how he might use WiGait in his own life. “I will want my parents to use it,” he says. “They live in Taiwan. I will want to use this to measure how well they are doing while Im not around them.”
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