» Articles » PMID: 28302596

Estimating Accuracy at Exercise Intensities: A Comparative Study of Self-Monitoring Heart Rate and Physical Activity Wearable Devices

Overview
Date 2017 Mar 18
PMID 28302596
Citations 101
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Physical activity tracking wearable devices have emerged as an increasingly popular method for consumers to assess their daily activity and calories expended. However, whether these wearable devices are valid at different levels of exercise intensity is unknown.

Objective: The objective of this study was to examine heart rate (HR) and energy expenditure (EE) validity of 3 popular wrist-worn activity monitors at different exercise intensities.

Methods: A total of 62 participants (females: 58%, 36/62; nonwhite: 47% [13/62 Hispanic, 8/62 Asian, 7/62 black/ African American, 1/62 other]) wore the Apple Watch, Fitbit Charge HR, and Garmin Forerunner 225. Validity was assessed using 2 criterion devices: HR chest strap and a metabolic cart. Participants completed a 10-minute seated baseline assessment; separate 4-minute stages of light-, moderate-, and vigorous-intensity treadmill exercises; and a 10-minute seated recovery period. Data from devices were compared with each criterion via two-way repeated-measures analysis of variance and Bland-Altman analysis. Differences are expressed in mean absolute percentage error (MAPE).

Results: For the Apple Watch, HR MAPE was between 1.14% and 6.70%. HR was not significantly different at the start (P=.78), during baseline (P=.76), or vigorous intensity (P=.84); lower HR readings were measured during light intensity (P=.03), moderate intensity (P=.001), and recovery (P=.004). EE MAPE was between 14.07% and 210.84%. The device measured higher EE at all stages (P<.01). For the Fitbit device, the HR MAPE was between 2.38% and 16.99%. HR was not significantly different at the start (P=.67) or during moderate intensity (P=.34); lower HR readings were measured during baseline, vigorous intensity, and recovery (P<.001) and higher HR during light intensity (P<.001). EE MAPE was between 16.85% and 84.98%. The device measured higher EE at baseline (P=.003), light intensity (P<.001), and moderate intensity (P=.001). EE was not significantly different at vigorous (P=.70) or recovery (P=.10). For Garmin Forerunner 225, HR MAPE was between 7.87% and 24.38%. HR was not significantly different at vigorous intensity (P=.35). The device measured higher HR readings at start, baseline, light intensity, moderate intensity (P<.001), and recovery (P=.04). EE MAPE was between 30.77% and 155.05%. The device measured higher EE at all stages (P<.001).

Conclusions: This study provides one of the first validation assessments for the Fitbit Charge HR, Apple Watch, and Garmin Forerunner 225. An advantage and novel approach of the study is the examination of HR and EE at specific physical activity intensities. Establishing validity of wearable devices is of particular interest as these devices are being used in weight loss interventions and could impact findings. Future research should investigate why differences between exercise intensities and the devices exist.

Citing Articles

Reliability and Accuracy of the Fitbit Charge 4 Photoplethysmography Heart Rate Sensor in Ecological Conditions: Validation Study.

Ceugniez M, Devanne H, Hermand E JMIR Mhealth Uhealth. 2025; 13():e54871.

PMID: 39789790 PMC: 11735015. DOI: 10.2196/54871.


Relationship between physical activity and biomarkers of pathology and neuroinflammation in preclinical autosomal-dominant Alzheimer's disease.

Guzman-Velez E, Rivera-Hernandez A, Fabrega S, Oliveira G, Martinez J, Baena A Alzheimers Dement (N Y). 2025; 10(4):e70003.

PMID: 39748841 PMC: 11694529. DOI: 10.1002/trc2.70003.


Within-person associations between daily stress and physical activity during working and non-working hours.

Courtney J, Turner J, Puterman E, Almeida D Psychol Sport Exerc. 2024; 76:102777.

PMID: 39551252 PMC: 11611609. DOI: 10.1016/j.psychsport.2024.102777.


Assessment of Physiological Signals from Photoplethysmography Sensors Compared to an Electrocardiogram Sensor: A Validation Study in Daily Life.

Rehman R, Chatterjee M, Manyakov N, Daans M, Jackson A, OBrisky A Sensors (Basel). 2024; 24(21).

PMID: 39517723 PMC: 11548599. DOI: 10.3390/s24216826.


Hyperactivity in ADHD: Friend or Foe?.

Hoy B, Bi M, Lam M, Krishnasamy G, Abdalmalak A, Fenesi B Brain Sci. 2024; 14(7).

PMID: 39061459 PMC: 11274564. DOI: 10.3390/brainsci14070719.


References
1.
Evenson K, Goto M, Furberg R . Systematic review of the validity and reliability of consumer-wearable activity trackers. Int J Behav Nutr Phys Act. 2015; 12:159. PMC: 4683756. DOI: 10.1186/s12966-015-0314-1. View

2.
Tucker J, Welk G, Beyler N . Physical activity in U.S.: adults compliance with the Physical Activity Guidelines for Americans. Am J Prev Med. 2011; 40(4):454-61. DOI: 10.1016/j.amepre.2010.12.016. View

3.
Spierer D, Rosen Z, Litman L, Fujii K . Validation of photoplethysmography as a method to detect heart rate during rest and exercise. J Med Eng Technol. 2015; 39(5):264-71. DOI: 10.3109/03091902.2015.1047536. View

4.
Adam Noah J, Spierer D, Gu J, Bronner S . Comparison of steps and energy expenditure assessment in adults of Fitbit Tracker and Ultra to the Actical and indirect calorimetry. J Med Eng Technol. 2013; 37(7):456-62. DOI: 10.3109/03091902.2013.831135. View

5.
Cadmus-Bertram L, Marcus B, Patterson R, Parker B, Morey B . Randomized Trial of a Fitbit-Based Physical Activity Intervention for Women. Am J Prev Med. 2015; 49(3):414-8. PMC: 4993151. DOI: 10.1016/j.amepre.2015.01.020. View