Evidence map›Paper›PMID 38276327›Full record

ArticleSensors (Basel, Switzerland)2024

Evaluating Accuracy in Five Commercial Sleep-Tracking Devices Compared to Research-Grade Actigraphy and Polysomnography.

Kyle A Kainec, Jamie Caccavaro, Morgan Barnes, Chloe Hoff, Annika Berlin, Rebecca M C Spencer

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 4 pooled it
26.4field-weighted citation impact, top 1% of its field
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

41 citing papers in PubMed, 4 syntheses or guidelines pooled it, 52 citations in OpenAlex.

  1. Pooled it
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  4. Performance of consumer wrist-worn sleep tracking devices compared to polysomnography: a meta-analysis.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025
    Pooled it
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  17. The effect of standard time to daylight-saving clock transition on sleep and migraine headaches.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2026
    Observational
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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

6 authors at 1 institution in 1 country.

Kyle A KainecNeuroscience & Behavior Program, French Hall, University of Massachusetts Amherst, 230 Stockbridge Road, Amherst, MA 01003, USA.ORCID 0000-0001-9200-9923
Jamie CaccavaroDepartment of Psychological and Brain Sciences, Tobin Hall, University of Massachusetts Amherst, 135 Hicks Way, Amherst, MA 01003, USA.
Morgan BarnesInstitute for Applied Life Sciences, Life Science Laboratories, University of Massachusetts Amherst, 240 Thatcher Road, Amherst, MA 01003, USA.
Chloe HoffInstitute for Applied Life Sciences, Life Science Laboratories, University of Massachusetts Amherst, 240 Thatcher Road, Amherst, MA 01003, USA.
Annika BerlinInstitute for Applied Life Sciences, Life Science Laboratories, University of Massachusetts Amherst, 240 Thatcher Road, Amherst, MA 01003, USA.
Rebecca M C SpencerNeuroscience & Behavior Program, French Hall, University of Massachusetts Amherst, 230 Stockbridge Road, Amherst, MA 01003, USA.
University of Massachusetts Amherst · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of consumer sleep-tracking technologies has outpaced the scientific evaluation of their accuracy. In this study, five consumer sleep-tracking devices, research-grade actigraphy, and polysomnography were used simultaneously to monitor the overnight sleep of fifty-three young adults in the lab for one night. Biases and limits of agreement were assessed to determine how sleep stage estimates for each device and research-grade actigraphy differed from polysomnography-derived measures. Every device, except the Garmin Vivosmart, was able to estimate total sleep time comparably to research-grade actigraphy. All devices overestimated nights with shorter wake times and underestimated nights with longer wake times. For light sleep, absolute bias was low for the Fitbit Inspire and Fitbit Versa. The Withings Mat and Garmin Vivosmart overestimated shorter light sleep and underestimated longer light sleep. The Oura Ring underestimated light sleep of any duration. For deep sleep, bias was low for the Withings Mat and Garmin Vivosmart while other devices overestimated shorter and underestimated longer times. For REM sleep, bias was low for all devices. Taken together, these results suggest that proportional bias patterns in consumer sleep-tracking technologies are prevalent and could have important implications for their overall accuracy.

Indexed as

ActigraphySleep Wake DisordersHumansPolysomnographyReproducibility of ResultsSleepSleep StagesYoung AdultactigraphyFitbitGarminOurapolysomnographysleepWithings

Identifiers

PMID38276327
PMCPMC10820351
OpenAlexW4391030541

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.