PALO ALTO, Calif. — Stanford cardiologist Alan Yeung has embarked on what may be the most audacious study of exercise in history. Using an app on those ubiquitous gadgets that many of us carry around 24/7 — our smartphones, fitness watches and other electronic devices — Yeung and his colleagues are mapping the second-by-second minutiae of how we move. Not just the count of our steps, but all sorts of measures, including our velocity and orientation in space.
Just a year in, the results already are provocative.
For starters, America’s couch-potato lifestyle may be worse than anyone thought. Not only are many of us not exercising, the early data also show that a huge percentage of us are barely moving. The finding applies even to people in their 20s through 40s, supposedly the prime of life.
“This was a surprise,” Yeung said. “A lot of people are spending most of their time sitting around — not even standing, not even going up and down.”
The numbers also confirm one of the nation’s cliched fitness divides, with East Coast residents being less active than their counterparts in California, Oregon and Washington state.
The study is one of a number of potentially paradigm-shifting initiatives made possible by the gazillion data points amassed by our smart devices. Stanford’s app — which participants download voluntarily — is part of the first generation of projects powered by Apple’s ResearchKit, a set of free tools introduced by the company in early 2015 to great fanfare and a fair amount of skepticism.
More than 100,000 people signed up in just the first six months, generating so much information that most of the researchers involved have been able to analyze only a tiny fraction of it.
Other apps in this first wave target asthma, melanoma, breast cancer, epilepsy, autism and Parkinson’s disease, capitalizing on the power of various tracking and multimedia features to extract information that might be helpful for researchers and participants alike. The Parkinson’s app uses a device’s touch screen to analyze a sequence of finger taps and determine whether they might signal tremors. Another tool lets you aim your smartphone camera at a child’s face while he or she watches a video, with the app then reading the youngster’s reaction to signal whether there might be concern about autism.
Stanford’s project uses a smartphone’s accelerometer (a sensor that measures movement and velocity) and gyroscope (which measures angular rotation across three axes) to analyze how we move. The researchers’ goal is to figure out how we can change our movements to improve heart health and live longer. Eventually, they hope to answer such questions as: Does a person need to exercise daily, or is it okay to be a weekend warrior? Are brief, high-intensity workouts just a fad, or do they actually work?
“We know exercise saves lives,” explained project co-director Euan Ashley, head of Stanford’s biomedical data science initiative. “What we don’t know is what is the right dose.”
Scientists’ aha! moment on the link between exercise and health came in 1953 with the publication of a study by Scottish epidemiologist Jeremiah Morris.
It focused on London’s transportation workers, who worked in pairs on the city’s double-decker buses. They worked the same shifts and breathed the same air, but there was one big difference. While drivers spent most of their time sitting, the conductors who walked up and down the aisles selling tickets climbed about 600 stairs each shift. In analyzing the health outcomes of the two groups, Morris found a startling disparity: Over a two-year period, the conductors were 50 percent less likely to have a heart attack than the drivers.
Others began to take notice. In 1966, President Lyndon B. Johnson created the first Presidential Physical Fitness Awards, and in 1968 Kenneth H. Cooper’s book “Aerobics” hit the bestseller charts, introducing a new word into the American lexicon. And thus the world of jogging/yoga/power walking/kickboxing/spinning/Zumba/CrossFit/video workouts was born.
But much of what we know about exercise remains a guess, based mostly on experiments from lab treadmills or ideas from often unreliable details recorded in people’s diaries and logbooks.
Take the number 10,000, which has come to represent the point at which exercise becomes enough to keep us healthy. According to public-education campaigns, social media and your Fitbit, if you walk or run 10,000 steps a day — about five miles, depending on your stride — you’re all good. Look at the science behind this idea, however, and you’ll find no magic digits.
Weirdly enough, that goal originated with the manpo-kei, a type of pedometer sold in Japan in the 1960s that literally translates to “10,000-steps meter.” The mark then took on a life of its own as researchers began to use it as a baseline in their experiments.
At Stanford, an interdisciplinary team is now launching all manner of experiments to figure out how much the quantitative and qualitative goals we’ve come to accept as truth are grounded in real science. Its experiments have volunteers donning various consumer-grade fitness bands, heart-rate monitors and pulse trackers, putting on oxygen masks and then playing basketball — so researchers can learn what happens to our bodies and how well the technology is tracking those changes. They are brainstorming other big ideas, too — studying activity patterns in diverse regions of the world by giving these devices to rural Africans, for example, and creating an app to provide early warning of a heart attack and then dial 911.
The group’s involvement with ResearchKit began after Ashley and a colleague spoke on a panel about the future of big data in medicine. A man and a woman from the audience approached them with an unusual proposition. “They said, ‘We can’t really tell you who we are, but we’d like to work with you,’ ” Ashley recalled.
The mystery couple, it turned out, worked for Apple. Stanford signed on to the effort, and then groups from Johns Hopkins, Duke and Oregon Health & Science universities and other institutions came onboard.
The scientists say they were attracted to the project because it allows participants to use their own technology to get direct feedback. In the case of Stanford’s MyHeartCounts, the app lets users test their fitness by modifying the standard six-minute walking test that physicians have administered for years. In the doctor’s office, a person is asked to walk as far as possible in that amount of time. On a smartphone, the app tracks how far you walk and gives feedback on how you did compared with others your age.
Using traditional methods for recruiting study volunteers — posting flyers with a tear-off slip showing a number for people to call if they’re interested in taking part — getting 10,000 participants might have taken well over a year. Using the app, which was promoted through social media, the Stanford researchers got that many people within the first 24 hours. As of this week, roughly 53,000 were enrolled. Most are in the United States, but some signed on from Great Britain and Hong Kong.
The sheer scale of the data gathered so far is bringing the Silicon Valley way of problem-solving to medical science. According to the old-school scientific method, a researcher starts with a hypothesis and tests it out in a systematic way by collecting the appropriate data. But to analyze the big data being collected in this Stanford initiative, it can be more efficient to work the opposite way: to start by looking for patterns and connections and use what’s found to hone in on a hypothesis.
Doing research via mobile phone and other devices isn’t perfect, though.
Sami Yli-Piipari, an assistant professor of kinesiology at the University of Georgia who focuses on children’s physical activity, said the accuracy and validity of the devices aren’t always reliable, and researchers can do very little to prevent participants from entering fake data. The ResearchKit approach also raises issues about participants’ privacy and data security.
Yet figuring out people’s movement habits may turn out to be the easy part. Translating that knowledge into usable advice for a populace reluctant to exercise promises to be a different challenge altogether.
“We’ve made a huge step forward in terms of being able to start seeing the variety of activities people are doing in their lives, but we still need more accurate information — and to do more research on how we can actually use this data to change behaviors,” said Yli-Piipari, who was not part of the Stanford team.