Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort
Open accessPublished version of a preprint
Abstract
The ability to measure physical activity through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown. The aim of this work is to assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework. We evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 ± 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination. Devices reported the lowest error for cycling and the highest for walking. Device error was higher for males, greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest. In conclusion, most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).
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Wearable devices have higher error during activity than at rest.
“Our analyses reinforces the growing body of research demonstrating that wearable devices have higher error during activity than at rest.8,11,35,38,39”
From Investigating sources of inaccuracy in wearable optical heart rate sensors (2020) · cites this paper as [11]
The Results (§3.2; page unavailable) report the opposite for energy expenditure: error was highest while sitting and lower during walking and running. The paper also finds that heart-rate error varies by activity rather than establishing that it is generally higher during activity than at rest (§3.1 and §3.4). (LLM, conf=0.87)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredApple Watch devices showed less than 5 bpm variation across skin tones.
“In contrast, Apple Watch devices were more consistent, with <5 bpm variation across skin tones, findings supported by Sañudo et al. (2019) and Shcherbina et al. (2017) [7,10].”
From Photoplethysmography in Diverse Skin Tones: Evaluating Bias in Smartwatch Health Monitoring (2025) · cites this paper as [10]
The Results (§3.1) report that the Apple Watch had the lowest overall heart-rate error among the tested devices, and the Discussion (§4) notes that participants varied in skin tone. But the paper reports error as a percentage, not a less-than-5-bpm variation across skin tones; it also notes that darker skin tone correlated with increased error across multiple devices. (LLM, conf=0.87)
Experimental — accuracy not yet measuredA 5% level of accuracy was adopted as the widely accepted acceptable limit.
“We adopted the widely accepted level of accuracy of 5% to be within the acceptable limits [16].”
From Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study (2018) · cites this paper as [16]
The Methods (§2.5, Error) set 5% error as within acceptable limits. But the paper calls statistical significance—not 5% measurement accuracy—a widely accepted standard, and the Discussion (§4) describes its clinically acceptable error threshold as a proposed standard. It therefore supports adopting the 5% limit, but not calling that accuracy limit widely accepted. (LLM, conf=0.87)
Experimental — accuracy not yet measuredIn recent studies involving predominantly steady-state aerobic activities, wrist-worn activity monitors have been shown to have reasonable accuracy in heart rate estimation (approximately 5% error) but a poor estimate of energy expenditure, where the error was found to be closer to approximately 30% with a negative bias.
“In recent studies involving predominantly steady-state aerobic activities, wrist-worn activity monitors have been shown to have reasonable accuracy in HR estimation (approximately 5% error) but a poor estimate of EE, where the error was found to be closer to approximately 30% with a negative bias [16,17].”
From Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study (2018) · cites this paper as [16]
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredHeart rate measurements from wearable devices are often less accurate during physical activity or cyclic wrist motions.
“Several studies have demonstrated that HR measurements from wearable devices are often less accurate during physical activity or cyclic wrist motions.”
From Investigating sources of inaccuracy in wearable optical heart rate sensors (2020) · cites this paper as [11]
The Discussion reports higher heart-rate error at higher intensity within each activity, and Results §3.1 reports more error during walking than cycling. But the paper does not assess cyclic wrist motions, and its Conclusions say heart-rate measurements were within an acceptable error range in most activity settings; it does not support a general claim that physical activity makes them less accurate. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Skin color could influence the accuracy of the HR measurement.
“It has been reported that skin color could influence the accuracy of the HR measurement [16], and future studies should report the Fitzpatrick skin tone scale to account for this limitation.”
From Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study (2018) · cites this paper as [16]
Many validation studies have questioned the accuracy of raw sensor data and software algorithms.
“Many validation studies have questioned the accuracy of raw sensor data and software algorithms92–94.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [92]
As the sensor directly depends on reflectance properties of the skin tissue, different skin colors may change the overall signal quality of the recorded PPG data.
“As the sensor directly depends on reflectance properties of the skin tissue, different skin colors may change the overall signal quality of the recorded PPG data49,50.”
From Data quality evaluation in wearable monitoring (2022) · cites this paper as [50]
Only a small handful of studies examine skin tone and accuracy rates directly.
“there are only a small handful of studies that examine skin tone and accuracy rates directly1–3,11”
From Response To: Investigating sources of inaccuracy in wearable optical heart rate sensors (2021) · cites this paper as [2]
Previously reported studies found that wearables using green light technology had larger error rates in tracking heart rate and energy expenditure for individuals with darker skin tones, especially if exercising.
“This finding is in contrast to previously reported studies finding wearables using green light technology had larger errors rates in tracking heart rate and energy expenditure for individuals with darker skin tones2, especially if exercising3.”
From Response To: Investigating sources of inaccuracy in wearable optical heart rate sensors (2021) · cites this paper as [2]
Due to technological limitations of Photoplethysmography (PPG) green light signaling, health constructs may not be as accurate for a population of people with darker skin tones.
“due to technological limitations of Photoplethysmography (PPG) green light signaling, these health constructs may not be as accurate for a population of people with darker skin tones2,3”
From Response To: Investigating sources of inaccuracy in wearable optical heart rate sensors (2021) · cites this paper as [2]
All five studies that compared manufacturers found the Apple Watch to be more accurate than the other commercial devices.
“Of those, all five found the Apple Watch to be more accurate than the other commercial devices [2, 9–12].”
From Accuracy of heart rate measurement with wrist-worn wearable devices in various skin tones: a systematic review (2023) · cites this paper as [11]
Four of the ten included studies reported statistically significant reductions in heart rate measurement accuracy in participants with darker skin tones compared to participants with lighter skin tones.
“Overall, four of the ten studies reported a significant reduction in accuracy of heart rate measurement with wearable devices in darker-skinned individuals, compared to participants with lighter skin tones.”
From Accuracy of heart rate measurement with wrist-worn wearable devices in various skin tones: a systematic review (2023) · cites this paper as [11]
Shcherbina et al. noted that smart watch device error was higher for darker skin tones, but the degree of this effect was not reported.
“Shcherbina et al. noted that smart watch device error was higher for darker skin tones, but the degree of this effect was not reported [11].”
From Accuracy of heart rate measurement with wrist-worn wearable devices in various skin tones: a systematic review (2023) · cites this paper as [11]
Wearable devices are not as accurate, and may not work at all, in people with darker skin tones.
“We note with deep concern that there is increasing evidence that these devices are not as accurate, and may not work at all, in people with darker skin tones [1, 2].”
From Limiting racial disparities and bias for wearable devices in health science research (2020) · cites this paper as [1]
When comparing the accuracy of commercial devices, a significantly higher device measurement error is seen in males than females for all devices.
“When comparing the accuracy of commercial devices as done by Shcherbina et al., a significantly higher device measurement error is seen in males than females for all devices [109].”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [109]
Some studies have used the gold-standard reference method of electrocardiogram, which directly measures heart rate via electrical impulses from the heart and is used for clinical accuracy.
“Although some studies have attempted to address wearable HR accuracy using the gold-standard reference method of ECG, which directly measures HR via electrical impulses from the heart and is used for clinical accuracy38–44”
From Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research (2020) · cites this paper as [42]
The Apple Watch has slightly greater accuracy than Fitbit devices (Apple Watch: −1.3 bpm, Fitbit: −9.3 bpm).
“with the Apple Watch having slightly greater accuracy than Fitbit devices (Apple Watch: −1.3 bpm, Fitbit: −9.3 bpm42–44)”
From Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research (2020) · cites this paper as [42]
Wearables detect heart rate with acceptable accuracy in both laboratory and real-world settings for research, but importantly not medical settings.
“These findings have led some researchers to conclude that wearables detect HR with acceptable accuracy in both laboratory and real-world settings for research, but importantly not medical settings38,42 as more research needs to be done.”
From Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research (2020) · cites this paper as [42]
Apple Watch models have lower overall error (1.20 to 6.70%) than Fitbit models (2.38 to 21.36%).
“as well as lower overall error with the Apple Watch models ranging from 1.20 to 6.70% error and Fitbit models ranging from 2.38 to 21.36% error39,42,45”
From Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research (2020) · cites this paper as [42]
Larger wrist circumference has been shown to be associated with reduced heart rate accuracy, although these outcomes have not been found in all studies.
“Larger wrist circumference has been shown to be associated with reduced HR accuracy42, although these outcomes have not been found in all studies44,46.”
From Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research (2020) · cites this paper as [42]
Higher body mass index, which likely covaries with larger wrist circumference, has been shown to be associated with reduced heart rate accuracy, although these outcomes have not been found in all studies.
“Higher body mass index, which likely covaries with larger wrist circumference as described above, has been shown to be associated with reduced HR accuracy42,62, although again these outcomes have not been found in all studies44,46.”
From Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research (2020) · cites this paper as [42]
Research has found higher device error in males compared to females.
“In addition, research has not always reported participant biological sex, but research has found higher device error in males compared to females42, indicating that participant biological sex should be collected and possibly controlled.”
From Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research (2020) · cites this paper as [42]
A third study found that measurement during walking, running, and cycling was more accurate for some devices than during sitting.
“a third found that measurement during walking, running, and cycling was more accurate for some devices than during sitting42”
From Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research (2020) · cites this paper as [42]
Most wrist-worn devices adequately measure heart rate in laboratory-based activities, but poorly estimate energy expenditure.
“Shcherbina et al. demonstrated that most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate energy expenditure and caution the use of those measurements as part of health improvement programs [144].”
From Wearables and the Medical Revolution (2018) · cites this paper as [144]
The present wearable technology is known to be less reliable for people with darker skin tones and higher body mass index (e.g., inaccurate HR measurement).
“Finally, the present wearable technology is known to be less reliable for people with darker skin tones and higher body mass index (eg, inaccurate HR measurement).30”
From Association of Demographic and Socioeconomic Indicators With the Use of Wearable Devices Among Children (2023) · cites this paper as [30]
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Validity of heart rate measurements in wrist-based monitors across skin tones during exercise
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Photoplethysmography in Diverse Skin Tones: Evaluating Bias in Smartwatch Health Monitoring
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- Authors
- Shcherbina, A., Mattsson, C., Waggott, D., Salisbury, H., Christle, J., Hastie, T., Wheeler, M., & Ashley, E.
- Affiliations
- Stanford Medicine (US)
- Swedish School of Sport and Health Sciences (SE)
- Stanford University (US)
- Corresponding author
- Ashley, Euan
- ORCID
- Venue
- Journal of Personalized Medicine
- Publisher
- MDPI AG
- Published
- 2017-05-24
- Volume
- 7
- Issue
- 2
- Pages
- 3
- ISSN
- 2075-4426 (ISSN-L)
- PMC
- PMC5491979
- OpenAlex
- W2618581983
- Cited by
- 625
- References
- 20
- Citations by year
- 2026: 64 · 2025: 63 · 2024: 52 · 2023: 71 · 2022: 74 · 2021: 79 · 2020: 72 · 2019: 90 · 2018: 50 · 2017: 9 · 2014: 1
- FWCI
- 27.19
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Personalized Medicine (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
- Funders
- Food And Drug Administration (125614)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Keywords
- wrist-worn devices, wearable sensors, heart rate measurement, energy expenditure estimation, device accuracy, consumer health devices, Apple Watch, Fitbit, indirect calorimetry, physical activity monitoring, skin tone, body mass index, sex differences, walking and cycling
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