Many machines can recognize humans by their fingerprints or facial features. These biometric traits are not the only ones that set individuals apart, however. Each person’s walking gait is unique—and they can serve not only as identifiers but also as indicators of mood and health. A team of researchers has now developed remote sensors that analyze footsteps by measuring minute floor vibrations. They have used those vibrations to identify specific individuals walking through a building and to test a new method of hands off health monitoring.

1. M E D I C A L & B I O T E C H
Footstep Sensors Identify People by Gait
The supersensitive system can also glean clues about health
By Sophie Bushwick on April 30, 2020
Each person’s walking gait is unique. Credit: Getty Images
Many machines can recognize humans by their fingerprints or facial features. These
biometric traits are not the only ones that set individuals apart, however. Each person’s
walking gait is unique—and they can serve not only as identifiers but also as indicators of
mood and health. A team of researchers has now developed remote sensors that analyze
footsteps by measuring minute floor vibrations. They have used those vibrations to identify
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2. specific individuals walking through a building and to test a new method of hands-off health
monitoring.
The way someone walks is “like a fingerprint—it’s like a very unique signature of yourself,”
says Hae Young Noh, who initially performed the research as a civil and environmental
engineer at Carnegie Mellon University and has since moved to Stanford University. It can
reveal “who you are, where you are, what kinds of activities you’re doing or even your
cognitive state.” If hardware sensors detect a pattern of footsteps, software can analyze them
to verify an individual’s identity. Similar systems have done so with 95 percent accuracy, says
Vir Phoha, a professor of electrical engineering and computer science at Syracuse University,
who was not involved in the new work.
And walking patterns can be more than a simple ID. “There is a lot of information you can
learn from a person’s gait—specifically, health-related information,” Phoha says. If somebody
starts placing more weight on one side or another, for example, the change in balance could
indicate a neurological problem. This information could help doctors monitor seniors and
other at-risk patients who want to live independently: tracking subjects’ gait could keep tabs
on their health without directly impinging on their space.
To measure this data-rich signature, researchers previously had to outfit subjects with
wearable devices or have them walk on special mats or altered flooring. But Noh, electrical
and computer engineer Pei Zhang of Carnegie Mellon and their colleagues decided to develop
footstep sensors that would work remotely. The scientists took advantage of the fact that
typical walls and floors pick up even faint vibrations from activity in the space they contain.
“We call this ‘structures as sensors,’ where we’re using these big physical structures like
buildings and bridges as a sensing system to indirectly monitor humans and surrounding
environments,” Noh says.
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3. Sensing vibrations from a mere footstep requires extremely sharp detectors. “To give you an
idea how sensitive our sensors are: when you sit in the chair a meter away, we put the sensor
on the ground,” Zhang says, and “we can sense your heartbeat.” Each sensor—a cylindrical
device with height of a few centimeters—sits on the floor and can pick up a walker at a
distance of up to 20 meters, Noh says. The researchers distribute such sensors as an array
throughout the area where they want to detect footsteps. But in a busy building, such acute
detectors would pick up a lot more. Thus, the team also had to “teach” the new system to
distinguish these signals from any background noise.
“Fighting the noise is the biggest challenge we have,” Noh says, and addressing it required
both hardware and software solutions. On the hardware side, each sensor has an amplifier
that can automatically change the amount of a footstep vibration it boosts. When one seems
to be coming from farther away, the amplifier turns it up. As the signal gets stronger and
threatens to overwhelm the sensor, the amplifier decreases its sensitivity. Noh likens this
process to remotely controlling the volume of a speaker: listeners make it louder when they
are farther away in order to hear better, but as they get closer, and the sound becomes too
intense, they dial it down.
Once the sensors have picked up a footstep, the software takes over. “We do various signal-
processing and machine-learning [techniques] to learn what is the human-related signal
versus other noise that we’re not interested in,” Noh says. Like the data from other footstep-
detection methods (such as wearables or pressure mats), walking patterns measured with
these sensors can be used to determine an individual’s identity and some kinds of potential
health issues. The team has presented its work at several conferences and seminars—most
recently at the Society for Experimental Mechanics’ It’s Not Just Modal Anymore conference
in February.
The way the system displays walkers’ behavior live on a computer monitor made one
researcher think of a more fantastical device. Eve Schooler, principal engineer and director of
emerging Internet of Things networks at Intel, says she was interested in creating a
technological version of the “Marauder’s Map”—a magical floor plan in the Harry Potter book
and film series that “uses footsteps to visually portray where people are.” In the real world,
such a device might track a building’s occupants and other objects in real time. Inspired by
Schooler’s suggestion, the Carnegie Mellon team made its own iteration, creating a digital
display that shows footprints appearing on a floor plan with the appearance of the magical
paper map.
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4. The fictional Marauder’s Map only portrayed one location, but the researchers’ portable
footstep sensors could be used in any building, Schooler notes. “Some of the algorithms that
they’ve developed make the result transferable, which is what’s so interesting,” she says. “You
don’t have to do all this calibration to figure out people’s signature across buildings—they
have the techniques to do that for you.” Once the experimental system “learned” a person’s
signature gait, the sensor array could recognize that individual at the office or home. Given
the devices’ affordability—Noh estimates each would cost about $10 to $20 to produce—and
the fact that they can be placed every 20 meters to create an image of an entire floor—the
wide range of applications Schooler suggests indeed seem possible.
The ability to conduct this kind of monitoring raises obvious privacy concerns, and the
researchers only suggest their technology should be used for consensual health care
applications. Such monitoring systems, they note, can help caregivers who need to know
when elderly patients might be likely to fall—or children’s hospitals that want to detect the
telltale signs of chronic diseases, such as muscular dystrophy, as soon as possible. For those
examples, developers assert, footstep sensors would preserve privacy better than, say, a
camera that also captures visual information. “This is actually created because of the privacy
concerns of the other type of monitoring mechanisms,” Zhang says. And in health-related
scenarios, he adds, “I’m willing to trade off a little bit of my data information to prevent falls
and to detect diseases.”
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Sophie Bushwick
Credit: Nick Higgins
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