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Accuracy Of Fitbit Activity Monitor To Predict Energy Expenditure With And Without Classification Of Activities: 725Board #2 8:00 AM - 10:00 AM

Dannecker, Kathryn L.; Petro, Sean A.; Melanson, Edward L. FACSM; Browning, Raymond C.

Medicine & Science in Sports & Exercise: May 2011 - Volume 43 - Issue 5 - p 62
doi: 10.1249/01.MSS.0000402857.55729.ab
E-16 Thematic Poster - Predicting Energy Expenditure: JUNE 3, 2011 8:00 AM - 10:00 AM: ROOM: 404
Free

1Colorado State University, Fort Collins, CO.2University of Colorado Denver, Denver, CO.

Email: kldannecker@gmail.com

(No relationships reported)

The Fitbit activity monitor is a consumer device for predicting energy expenditure (EE) and tracking activity patterns. To improve the EE estimation accuracy, Fitbit provides a web-based software program that allows a user to classify periods as distinct activities (based on the compendium of physical activities). However, the effect of this manual activity classification on EE estimation accuracy is not known.

PURPOSE: To compare the EE prediction accuracy of the Fitbit before and after classifying activities.

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METHODS: Fifteen adults (7 male), 71.91(17.3) kg, 24.17(3.9) kg/m2, completed a four hour stay in a room calorimeter. Participants wore Fitbit on the right hip, and performed a series of randomly assigned activities/postures including supine, seated (quietly and using a computer), standing, walking, stepping, cycling, sweeping, and self-selected activities. We used the web-based software to classify each activity, and compared the estimated EE to the measured EE before and after activity classification.

RESULTS: Without activity classification, Fitbit significantly underestimated EE (368(18) vs. 499(24)kcal, mean(SE)). Classifying activities resulted in improved estimates of EE (516(13) vs. 499(24)kcal, mean(SE)). Root mean square error for non-classified EE was 136.7kcals (27.4%) and was reduced to 64.25kcals (12.9%) with activity classification. The non-classification estimates always underestimated EE, while the classified values were underestimated about half of the time, and were more accurate in all but two subjects.

CONCLUSIONS: Fitbit is most accurate when the time is taken to classify the activities that were performed while wearing the device, though this may not be practical for the average consumer.

© 2011 American College of Sports Medicine