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. 2016 May 27;11(5):e0154420.
doi: 10.1371/journal.pone.0154420. eCollection 2016.

Accuracy of Heart Rate Watches: Implications for Weight Management

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Accuracy of Heart Rate Watches: Implications for Weight Management

Matthew P Wallen et al. PLoS One. .

Abstract

Background: Wrist-worn monitors claim to provide accurate measures of heart rate and energy expenditure. People wishing to lose weight use these devices to monitor energy balance, however the accuracy of these devices to measure such parameters has not been established.

Aim: To determine the accuracy of four wrist-worn devices (Apple Watch, Fitbit Charge HR, Samsung Gear S and Mio Alpha) to measure heart rate and energy expenditure at rest and during exercise.

Methods: Twenty-two healthy volunteers (50% female; aged 24 ± 5.6 years) completed ~1-hr protocols involving supine and seated rest, walking and running on a treadmill and cycling on an ergometer. Data from the devices collected during the protocol were compared with reference methods: electrocardiography (heart rate) and indirect calorimetry (energy expenditure).

Results: None of the devices performed significantly better overall, however heart rate was consistently more accurate than energy expenditure across all four devices. Correlations between the devices and reference methods were moderate to strong for heart rate (0.67-0.95 [0.35 to 0.98]) and weak to strong for energy expenditure (0.16-0.86 [-0.25 to 0.95]). All devices underestimated both outcomes compared to reference methods. The percentage error for heart rate was small across the devices (range: 1-9%) but greater for energy expenditure (9-43%). Similarly, limits of agreement were considerably narrower for heart rate (ranging from -27.3 to 13.1 bpm) than energy expenditure (ranging from -266.7 to 65.7 kcals) across devices.

Conclusion: These devices accurately measure heart rate. However, estimates of energy expenditure are poor and would have implications for people using these devices for weight loss.

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Conflict of interest statement

Competing Interests: The principal investigator on the study (Coombes) received an unrestricted grant from Coca Cola that was used to partially fund this study. The purpose of the financial support was to support research investigating the effects of high intensity exercise on energy balance in participants with the metabolic syndrome. To assess energy expenditure we first wanted to conduct a sub-study to investigate the accuracy of wrist worn devices to collect these data – leading to the submitted manuscript. As an unrestricted grant, Coca Cola had no input or control over any aspect of the study. Our only obligation/communication to Coca Cola regarding this study is to notify them of what we had done. This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials. Professor Wisløff (co-investigator on the study) is Director of a company (Beatstack) that has developed and patented a smart phone application called the ‘Personal Activity Intelligence, PAI’. Beatstack is now partially owned by Mio Global. This has led to the PAI app only being able to utilise heart rate data from Mio devices. Mio are developing more wrist worn heart rate devices (as would be most similar companies) and Professor Wisløff is working with the company to develop these products as part of his involvement in the Beatstack company and his interests in the PAI app. None of the Beatstack products or the Mio company had any involvement in the study. This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. Study protocol (58 mins in total).
Fig 2
Fig 2
Bland-Altman analyses comparing devices with reference method for (A) heart rate and (B) energy expenditure. Mean difference is indicated by the solid dot, with the lines indicating the 95% limits of agreement. Notes: HR = heart rate, kcal = kilocalories, bpm = beat per minute. Where mean difference or limits of agreement were systematically biased, point estimates were calculated using the mean value for the average of the two measures (device and reference).
Fig 3
Fig 3
Bland-Altman plots for device [(A) Apple Watch; N = 22, (B) Fitbit Charge HR; N = 22, (C) Samsung Gear S; N = 22, (D) Mio ALPHA; N = 22] and electrocardiography (reference) average heart rate (bpm). The solid line represents the mean difference (bpm) between the two measures and the dashed lines are the 95% limits of agreement (bpm). Notes: bpm = beats per minute, LoA = limits of agreement, MD = mean difference.
Fig 4
Fig 4
Bland-Altman plots for device [(A) Apple Watch; N = 22, (B) Fitbit Charge HR; N = 22, (C) Samsung Gear S; N = 19, (D) Mio ALPHA; N = 22] and METAMAX (reference) total energy expenditure (kcal). The solid line represents the mean difference (kcal) between the two measures and the dashed lines are the 95% limits of agreement (kcal). Notes: kcal = kilocalories, LoA = limits of agreement, MD = mean difference.
Fig 5
Fig 5
Bland-Altman plots for device [(A) Apple Watch; N = 21, (B) Fitbit Charge HR; N = 21, (C) Samsung Gear S; N = 20] and direct observation (reference) steps. The solid line represents the mean difference (steps) between the two measures and the dashed lines are the 95% limits of agreement (steps). Notes: LoA = limits of agreement, MD = mean difference.

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Grants and funding

The principal investigator on the study (Coombes) received an unrestricted grant from Coca Cola that was used to partially fund this study (Research Master Number 2014002786, http://transparency.coca-colajourney.com.au). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There was no additional external funding received for this study.
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