Mobile data: Made to measure

Neil Savage in Nature: “For decades, doctors around the world have been using a simple test to measure the cardiovascular health of patients. They ask them to walk on a hard, flat surface and see how much distance they cover in six minutes. This test has been used to predict the survival rates of lung transplant candidates, to measure the progression of muscular dystrophy, and to assess overall cardiovascular fitness.

The walk test has been studied in many trials, but even the biggest rarely top a thousand participants. Yet when Euan Ashley launched a cardiovascular study in March 2015, he collected test results from 6,000 people in the first two weeks. “That’s a remarkable number,” says Ashley, a geneticist who heads Stanford University’s Center for Inherited Cardiovascular Disease. “We’re used to dealing with a few hundred patients, if we’re lucky.”

Numbers on that scale, he hopes, will tell him a lot more about the relationship between physical activity and heart health. The reason they can be achieved is that millions of people now have smartphones and fitness trackers with sensors that can record all sorts of physical activity. Health researchers are studying such devices to figure out what sort of data they can collect, how reliable those data are, and what they might learn when they analyse measurements of all sorts of day-to-day activities from many tens of thousands of people and apply big-data algorithms to the readings.

By July, more than 40,000 people in the United States had signed up to participate in Ashley’s study, which uses an iPhone application called MyHeart Counts. He expects the numbers to surge as the app becomes more widely available around the world. The study — designed by scientists, approved by institutional review boards, and requiring informed consent — asks participants to answer questions about their health and risk factors, and to use their phone’s motion sensors to collect data about their activities for seven days. They also do a six-minute walk test, and the phone measures the distance they cover. If their own doctors have ordered blood tests, users can enter information such as cholesterol or glucose measurements. Every three months, the app checks back to update their data.

Physicians know that physical activity is a strong predictor of long-term heart health, Ashley says. But it is less clear what kind of activity is best, or whether different groups of people do better with different types of exercise. MyHeart Counts may open a window on such questions. “We can start to look at subgroups and find differences,” he says.

“You can take pretty noisy data, but if you have enough of it, you can find a signal.”

It is the volume of the data that makes such studies possible. In traditional studies, there may not be enough data to find statistically significant results for such subgroups. And rare events may not occur in the smaller samples, or may produce a signal so weak that it is lost in statistical noise. Big data can overcome those problems, and if the data set is big enough, small errors can be smoothed out. “You can take pretty noisy data, but if you have enough of it, you can find a signal,” Ashley says….(More)”.