echnology has become an indispensible part of
modern health care. But with technology come
data — a lot of it. Now armed with a grant from the
National Institutes of Health (NIH), psychologists,
NIH awarded a four-year, $10.8 million grant to establish
the National Center of Excellence for Mobile Sensor Data-
to-Knowledge (MD2K), based at the University of Memphis.
The project is just one component of NIH’s Big Data to
Knowledge initiative, which aims to translate vast biomedical
datasets into actionable health information.
Wearable devices such as the FitBit — a wristband that
tracks activity levels and sleep — have become popular with
consumers. But behavioral health researchers see even bolder
opportunities for mobile sensors.
“There are a lot of opportunities in terms of how this
technology can help people who are struggling with certain
health behaviors, and also help their health providers keep
better tabs on them,” says Gayle Beck, PhD, a University of
Memphis psychologist who is participating in the project.
MD2K focuses on two health concerns: congestive heart
failure and smoking cessation. Both, of course, have strong
behavioral components. And researchers believe that data
from sensors can ultimately help change those behaviors for
Sensors can gather physiological data about respiration,
heart rate and skin conductance (a measure of stress). They
can detect motions, such as the wrist movements associated
with smoking. With technology such as GPS and wireless
cameras, sensors could even detect whether, say, a heart-disease patient is approaching a doughnut shop, or an ex-
To learn more about the project, go to the Mobile
Sensor Data-to-Knowledge website at https://
md2k.org or to NIH’s Big Data to Knowledge
website at http://bd2k.nih.gov.
smoker is heading toward a bench where co-workers are
lighting up cigarettes.
Collecting data is relatively easy. Making sense of reams of
data is the challenge, says Mustafa al’Absi, PhD, a psychologist
at the University of Minnesota Medical School who is
participating in the smoking component of the project. His
lab is focused on developing reliable physiological measures
that can be linked to certain behaviors or emotional states.
“We are trying to develop a model whereby we can predict
times when people are tempted to smoke or to drink or even
to eat,” he says.
That’s where computer scientists and statisticians come in.
Together, the interdisciplinary MD2K team hopes to identify
reliable patterns of activity that suggest when a person might
be experiencing a craving. “Craving is a state of mind, but a
state of biology, too,” al’Absi says.
Ultimately, the researchers expect the technology will
provide valuable feedback both to patients and to their
health-care providers. “The intention is for it to become a
two-way street,” Beck says.
Imagine a smoker who is showing signs of stress. The sensor
device might start flashing or beeping, warning that she’s at risk
of lighting up. She might even receive a supportive text message
or phone call from a health coach. “The notion is to provide
immediate feedback to people, possibly before they recognize
that they’re at increased risk,” Beck says.
As long as there is a guarantee of data privacy, participants
in pilot studies have been willing to have their activities
tracked, Beck says. “Participants seem to be living their lives
and doing the things they’re used to doing.”
“It’s amazing how receptive people are to mobile
technology — even generations that didn’t grow up with
technology,” al’Absi adds. “That bodes well for the option of
While it takes some effort for researchers from such diverse
fields to learn a common language, M2DK’s interdisciplinary
approach is vital for tackling the big challenges of
understanding and applying large data sets, says Wendy
Nilsen, PhD, a health scientist administrator at the NIH Office
of Behavioral and Social Sciences Research. “There’s such a
huge space for psychology in this. When computer science,
engineering and behavior all come together, that’s where the
real power is.” n
participating in an NIH
project to collect health
data from wearable sensors.
By Kirsten Weir