Overview

• Current wrist-worn fitness trackers often misestimate calorie burn in individuals with obesity due to differences in gait and energy expenditure patterns.
• Northwestern researchers used data from commercial devices alongside metabolic carts and wearable cameras to validate the new dominant-wrist algorithm.
• In real-world and controlled settings the model estimated minute-by-minute energy expenditure with more than 95% accuracy for participants with obesity.
• The open-source algorithm is transparent and rigorously testable, inviting further research and development from other teams.
• Researchers plan to integrate the model into an activity-monitoring app for iOS and Android that will debut later this year.