Fitness Watches Overestimate Calories by Up to 25 Percent

A new study reveals significant inaccuracies in popular fitness trackers, warning users that reliance on these devices for weight management can lead to unintended calorie surpluses.
Popular fitness watches frequently overestimate the number of calories a user burns during exercise, according to a new study from Florida International University. The research team tested devices from Apple, Garmin, Samsung, and Fitbit against clinical laboratory equipment and found that error rates often ranged between 15 and 25 percent. This means that the workout data many people rely on for daily energy tracking is significantly less precise than previously assumed.
For individuals trying to manage their weight, these errors can have practical consequences. If a watch reports that a user burned 500 calories when they actually burned only 375, the person might consume an extra 125 calories while believing they remain in a deficit. Over time, this discrepancy can lead to an unintentional calorie surplus, undermining weight loss goals. The study highlights that while these devices are useful for monitoring activity trends, their specific calorie counts should not be treated as exact clinical measurements.
Accuracy Varies Across Major Brands
The study identified clear differences in performance among the major manufacturers. Apple devices were found to be the most accurate in the group, while Garmin and Samsung devices showed the highest tendency to overestimate energy expenditure. Fitbit devices fell in the middle of the range. The researchers noted that no brand was perfectly reliable, suggesting that users should not assume any single brand provides a definitive truth about their metabolic output.
Jason Kostrna, the lead author of the study and an associate professor of kinesiology at FIU, emphasized that the calorie burn numbers should not be viewed as precise facts. He explained that being off by hundreds of calories each week is common. This margin of error is particularly problematic for people who use these numbers to justify additional food intake after a workout, as the perceived effort may not match the actual energy spent.
Body Composition Affects Error Rates
One of the most significant findings of the research was the correlation between body composition and accuracy. The study found that as a person's body fat percentage increased, the error in calorie estimation also tended to grow. This means that the demographic most likely to be using fitness trackers for weight management purposes may be receiving the least accurate data. The algorithms used by these devices appear to struggle more with estimating energy expenditure in individuals with higher body mass indices.
This creates a paradox where the tool is most needed by those who receive the least reliable information from it. While the devices remain valuable for tracking heart rate, sleep, and general activity levels, their calorie calculation features are subject to significant biological variables that the sensors cannot fully capture. Users are advised to use these numbers as a rough guide rather than a strict accounting tool for dietary planning.
Practical Implications for Daily Tracking
Experts suggest that users should adopt a more conservative approach to interpreting their fitness data. Rather than using the watch's calorie count to adjust daily food intake dynamically, it is better to view the number as a general indicator of activity level. For serious weight management, consulting with a healthcare provider or using more controlled measurement methods may be necessary to avoid the pitfalls of inconsistent device data.
The findings from the Florida International University study, reported by GN auto tech/wearables, serve as a reminder that consumer technology has limits. While smartwatches have democratized access to health data, they are not medical-grade instruments. Understanding the trade-offs between convenience and accuracy is essential for anyone relying on these devices to make long-term health decisions.






