Evidence map›Paper›PMID 41703347›Full record

ArticleJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2026

Validation of an artificial intelligence based single-channel photoplethysmography home sleep apnea test.

Nathaniel F Watson, Yoav Nygate, Sam Rusk, Matt Sprague, Tom Vanasse, Jan Wodnicki, Fred Turkington, Kelsey Buehl, Andrea Ramberg, Leah Kisling and 3 more

Abstract readValidation Study
In one paragraph

Article in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Nathaniel F WatsonDepartment of Neurology, University of Washington School of Medicine, Seattle, WA, USA. nwatson@uw.edu.ORCID http://orcid.org/0000-0003-4870-080X
Yoav NygateEnsoData, Madison, WI, USA.
Sam RuskEnsoData, Madison, WI, USA.
Matt SpragueEnsoData, Madison, WI, USA.
Tom VanasseEnsoData, Madison, WI, USA.
Jan WodnickiEnsoData, Madison, WI, USA.
Fred TurkingtonEnsoData, Madison, WI, USA.
Kelsey BuehlEnsoData, Madison, WI, USA.
Andrea RambergEnsoData, Madison, WI, USA.
Leah KislingEnsoData, Madison, WI, USA.
Nick GlattardEnsoData, Madison, WI, USA.
Justin MortaraEnsoData, Madison, WI, USA.
Chris FernandezEnsoData, Madison, WI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

objectivesTo validate EnsoSleep photoplethysmography (ePPG) software as a medical device (SaMD) for home sleep apnea testing compared to polysomnography.

methodsSimultaneous polysomnography (PSG) and photoplethysmography (PPG) signals were recorded for a single night in 225 individuals at risk for obstructive sleep apnea (OSA). PSG was scored by three registered polysomnographic technologists and reviewed by a board-certified sleep specialist for fidelity. The ePPG studies were scored via a machine learning (ML) based scoring module. McNemar’s test, Deming regression, Bland-Altman plots, and sensitivity and specificity were used to compare ePPG to PSG. In addition to AHI, we also assessed total sleep time, sleep efficiency, sleep latency, wake after sleep onset, and sleep architecture.

resultsMcNemar’s test resulted in a p-value of 0.511, suggesting no systematic differences between the measurements. For ePPG, the mean difference in 3% AHI, compared to PSG, was 0.74 higher (95% CI: 0.43, 1.06) apneas and hypopneas per hour of sleep. The OSA classification 3% AHI sensitivity was 90.9% (95% CI: 86.3%, 95.4%), with a specificity of 72.3% (95% CI: 62.5%, 81.9%). The mean difference between PSG and ePPG was − 2.94 min (95% CI: -4.44, -1.62) for total sleep time, -9.9 min for sleep latency (95% CI: -10.80, -8.52), 9.42 min (95% CI: 8.34, 10.62) for wake after sleep onset, and − 0.6% (95% CI: -1.0%, -0.3%) for sleep efficiency.

conclusionsThis research demonstrated that ePPG SaMD is non-inferior to other home sleep apnea test (HSAT) options as an aid in the diagnosis of OSA.

Indexed as

Artificial IntelligencePhotoplethysmographySleep Apnea, ObstructiveAdultFemaleHumansMaleMiddle AgedPolysomnographyReproducibility of ResultsSensitivity and SpecificityHome sleep apnea testingMcNemar’s testPolysomnographySleep architectureValidation

Identifiers

PMID41703347
PMCPMC12995006

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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.