Evidence map›Paper›PMID 39362983›Full record

ArticleScientific reports2024

Accuracy of smartwatches for the remote assessment of exercise capacity.

Alexandra Jamieson, Siana Jones, Nishi Chaturvedi, Alun D Hughes, Michele Orini

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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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

5 authors.

Alexandra JamiesonMRC Unit for Lifelong Health and Ageing, UCL, 5th Floor, 1-19 Torrington Place, London, WC1E 7HB, UK. alexandra.jamieson@ucl.ac.uk.
Siana JonesMRC Unit for Lifelong Health and Ageing, UCL, 5th Floor, 1-19 Torrington Place, London, WC1E 7HB, UK.
Nishi ChaturvediMRC Unit for Lifelong Health and Ageing, UCL, 5th Floor, 1-19 Torrington Place, London, WC1E 7HB, UK.
Alun D HughesMRC Unit for Lifelong Health and Ageing, UCL, 5th Floor, 1-19 Torrington Place, London, WC1E 7HB, UK.
Michele OriniMRC Unit for Lifelong Health and Ageing, UCL, 5th Floor, 1-19 Torrington Place, London, WC1E 7HB, UK.

Funding

British Heart Foundation AA/18/6/34223British Heart Foundation FS/19/63/34902British Heart Foundation SP/F/21/150020Medical Research Council MC_UU_12019/1Wellcome Trust
6 · The paper itself

Abstract

Exercise capacity is a strong independent predictor of cardiovascular and all-cause mortality. The utilization of well-established submaximal tests of exercise capacity such as the 6-min walk test (6MWT), 3-min step test (3MST) and 10-chair rise test (10CRT) in the community would improve patient care but requires remote monitoring technology. Consumer grade smartwatches provide such an opportunity, however, their accuracy in measuring physiological responses to these tests is unclear. The aim of this study was to determine the accuracy of consumer grade smartwatches in assessing exercise capacity to develop a framework for remote, unsupervised testing. 16 healthy adults (7 male (44%), age median 27 [interquartile range (IQR) 26,29] years) performed 6MWTs using two protocols: (1) standard-straight 30 m laps (6MWT-standard) and 2) continuous lap-circular 240 m laps around a park (6MWT-continuous lap), 3MSTs and 10CRTs. Each one of these four tests was performed three times across two clinic visits. Each participant was fitted with a Garmin Vivoactive4 and Fitbit Sense smartwatch to measure three parameters: distance, step counts and heart rate (HR) response. Reference measures were a meter-wheel, hand tally counter and ECG, respectively. Mean HR was measured at rest, peak exercise and recovery. Agreement was measured using Bland-Altman analysis for repeated measures and summarized as median absolute percentage errors (MAPE). Distance during 6MWT-continuous lap had better agreement than during 6MWT-standard for both Garmin (MAPE: 6.4% [3.0, 10.4%] versus 20.1% [13.9, 28.4%], p < 0.001) and Fitbit (8.0% [2.9, 10.1% versus 18.8% [15.2, 28.1%], p < 0.001). Garmin measured step count more accurately than Fitbit (MAPE: 1.8% [0.9, 2.9%] versus 8.0% [2.6, 12.3%], p < 0.001). Irrespective of test, both devices showed excellent accuracy in measuring HR at rest and recovery (≤ 3%), while accuracy decreased during peak exercise (Fitbit: ~ 12% and Garmin: ~ 7%). In young adults without mobility difficulties, exercise capacity can be measured remotely using standardized tests and consumer grade smartwatches.

Indexed as

Heart RateAdultExerciseExercise TestExercise ToleranceFemaleHumansMaleWalk TestWearable Electronic Devices

Identifiers

PMID39362983
PMCPMC11452199

What OpenQuestion holds

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Registered trials

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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.