Existing fitness apps can make people with obesity feel trapped and often fail to measure their physical activity accurately, say scientists from Northwestern University. Now, they believe they’ve found a solution.
The Northwestern researchers have developed a new algorithm that takes into account the differences in gait, walking speed, and energy burned by people with obesity – something a typical fitness app would overlook.
Their work bridges a “critical” gap in fitness technology, according to Nabil Alshurafa, whose Northwestern lab created and tested the open-source, dominant-wrist algorithm specifically tuned for those with obesity.
The algorithm enables smartwatches to more accurately monitor the calories burned by people in larger bodies during various physical activities.
"Fitness shouldn’t feel like a trap for the people who need it most,"
says Northwestern's Nabil Alshurafa.
According to Alshurafa, their work was driven by personal experience. He was motivated to create an algorithm after attending an exercise class with his mother-in-law, who has obesity.
“She worked harder than anyone else, yet when we glanced at the leaderboard, her numbers barely registered,” Alshurafa said.
“That moment hit me: fitness shouldn’t feel like a trap for the people who need it most,” he added.
Northwestern claims the model, detailed in Nature Scientific Reports, is transparent and “rigorously testable." As an open-source model, it is ready for other researchers to build upon.
The researchers are currently working to launch their new fitness app for both iOS and Android later this year.
“People with obesity could gain major health insights from activity trackers, but most current devices miss the mark,” said Alshurafa, associate professor of behavioral medicine at Northwestern University Feinberg School of Medicine.
Current activity-monitoring algorithms used by fitness trackers were built for people without obesity and often misread energy expenditure in people with higher body weight.
“Without a validated algorithm for wrist devices, we’re still in the dark about exactly how much activity and energy people with obesity really get each day, slowing our ability to tailor interventions and improve health outcomes,” Alshurafa said.
The researchers tested their algorithm using data from commercial fitness trackers, with results showing it was over 95% more accurate in real-world situations.
In test runs, Alshurafa said he would challenge study participants to do as many pushups as they could in five minutes.
“Many couldn’t drop to the floor, but each one crushed wall-pushups, their arms shaking with effort,” he said.
“We celebrate ‘standard’ workouts as the ultimate test, but those standards leave out so many people. These experiences showed me we must rethink how gyms, trackers, and exercise programs measure success – so no one’s hard work goes unseen.”
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