Fitness Tracker Data Gets Personal

Today’s activity trackers accumulate enormous amounts of information. The challenge, however, is how to convert that fitness tracker data into an effective tool that promotes health behavioral changes and improvements.

Penn State University researchers in University Park have developed a method to leverage fitness tracker data to create tailored digital messages specific to the wearer. The goal is to learn from reactions to specific digital messages over time and then continue to deliver prompts in the correct context at a time and frequency and that successfully triggers the desired health activity.

For example, an activity tracker that uses this program can record whether a prompt to move more is most effective on a rainy day, a hot day or a cold day. Then, when the weather matches the recorded history, the device delivers a message to get moving at the correct time and context that’s likely to prompt the desired behavior. While researchers acknowledge that some users may have privacy concerns, devices can be adjusted to restrict what information is shared.

“We’re using those models [from control engineering] to design feedback controllers that take into account the current state of the person and, together with the model, decide what the best time to send the messages,” said study author Constantino Lagoa, PhD, professor in the school of electrical engineering and computer science.

The study is published in Health Psychology (2021; 40 [8], 502–12).

See also: Tracker Information Motivates