Evidence map›Paper›PMID 30530451›Full record

ArticleJMIR mHealth and uHealth2018

Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study.

Ravi Kondama Reddy, Rubin Pooni, Dessi P Zaharieva, Brian Senf, Joseph El Youssef, Eyal Dassau, Francis J Doyle Iii, Mark A Clements, Michael R Rickels, Susana R Patton and 3 more

Registry-linked trialAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06103305 (Risk Stratifications for Patients Come With Palpitations in Assiut and Suez Canal University Hospitals), which is not on this map. Cited by 89 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
89citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06103305 not yet recruitingnot on this mapstarted 2024, after this paper: background citation

Risk Stratifications for Patients Come With Palpitations in Assiut and Suez Canal University Hospitals

TypeobservationalSponsorAssiut UniversityRan2024 to 2026Enrolled208ConditionsArrhythmias, Cardiac
3 · Its place in the literature

Who cites it

89 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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29 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Ravi Kondama ReddyDepartment of Biomedical Engineering, Oregon Health & Science University, Portland, OR, United States.ORCID http://orcid.org/0000-0001-9612-1314
Rubin PooniSchool of Kinesiology and Health Science, York University, Toronto, ON, Canada.ORCID http://orcid.org/0000-0002-8514-1405
Dessi P ZaharievaSchool of Kinesiology and Health Science, York University, Toronto, ON, Canada.ORCID http://orcid.org/0000-0002-9374-8469
Brian SenfHarold Schnitzer Diabetes Health Center, Oregon Health & Science University, Portland, OR, United States.ORCID http://orcid.org/0000-0002-0537-8243
Joseph El YoussefHarold Schnitzer Diabetes Health Center, Oregon Health & Science University, Portland, OR, United States.ORCID http://orcid.org/0000-0003-1618-8290
Eyal DassauHarvard John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, United States.ORCID http://orcid.org/0000-0001-5333-6892
Francis J Doyle IiiHarvard John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, United States.ORCID http://orcid.org/0000-0002-3293-9114
Mark A ClementsChildren's Mercy Kansas City, Kansas City, MO, United States.ORCID http://orcid.org/0000-0002-2368-0331
Michael R RickelsInstitute for Diabetes, Obesity & Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.ORCID http://orcid.org/0000-0002-9253-838X
Susana R PattonDepartment of Pediatrics, University of Kansas Medical Center, Kansas City, KS, United States.ORCID http://orcid.org/0000-0002-8902-6965
Jessica R CastleHarold Schnitzer Diabetes Health Center, Oregon Health & Science University, Portland, OR, United States.ORCID http://orcid.org/0000-0003-1179-5374
Michael C RiddellSchool of Kinesiology and Health Science, York University, Toronto, ON, Canada.ORCID http://orcid.org/0000-0001-6556-7559
Peter G JacobsDepartment of Biomedical Engineering, Oregon Health & Science University, Portland, OR, United States.ORCID http://orcid.org/0000-0001-9897-4783

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWrist-worn activity monitors are often used to monitor heart rate (HR) and energy expenditure (EE) in a variety of settings including more recently in medical applications. The use of real-time physiological signals to inform medical systems including drug delivery systems and decision support systems will depend on the accuracy of the signals being measured, including accuracy of HR and EE. Prior studies assessed accuracy of wearables only during steady-state aerobic exercise.

objectiveThe objective of this study was to validate the accuracy of both HR and EE for 2 common wrist-worn devices during a variety of dynamic activities that represent various physical activities associated with daily living including structured exercise.

methodsWe assessed the accuracy of both HR and EE for two common wrist-worn devices (Fitbit Charge 2 and Garmin vívosmart HR+) during dynamic activities. Over a 2-day period, 20 healthy adults (age: mean 27.5 [SD 6.0] years; body mass index: mean 22.5 [SD 2.3] kg/m

resultsFitbit and Garmin were reasonably accurate at measuring HR but with an overall negative bias. There was more error observed during high-intensity activities when there was a lack of repetitive wrist motion and when the exercise mode indicator was not used. The Garmin estimated HR with a mean relative error (RE, %) of -3.3% (SD 16.7), whereas Fitbit estimated HR with an RE of -4.7% (SD 19.6) across all activities. The highest error was observed during high-intensity intervals on bike (Fitbit: -11.4% [SD 35.7]; Garmin: -14.3% [SD 20.5]) and lowest error during high-intensity intervals on treadmill (Fitbit: -1.7% [SD 11.5]; Garmin: -0.5% [SD 9.4]). Fitbit and Garmin EE estimates differed significantly, with Garmin having less negative bias (Fitbit: -19.3% [SD 28.9], Garmin: -1.6% [SD 30.6], P<.001) across all activities, and with both correlating poorly with indirect calorimetry measures.

conclusionsTwo common wrist-worn devices (Fitbit Charge 2 and Garmin vívosmart HR+) show good HR accuracy, with a small negative bias, and reasonable EE estimates during low to moderate-intensity exercise and during a variety of common daily activities and exercise. Accuracy was compromised markedly when the activity indicator was not used on the watch or when activities involving less wrist motion such as cycle ergometry were done.

Indexed as

artificial pancreasenergy metabolismfitness trackersheart ratehigh-intensity interval training

Identifiers

PMID30530451
PMCPMC6305876

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.