Evidence map›Paper›PMID 40292768›Full record

ArticleSensors (Basel, Switzerland)2025

Detection and Severity Classification of Sleep Apnea Using Continuous Wearable SpO

Nhung H Hoang, Zilu Liang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Article
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

2 authors.

Nhung H HoangUbiquitous and Personal Computing Lab, Kyoto University of Advanced Science (KUAS), Kyoto 615-8577, Japan.
Zilu LiangUbiquitous and Personal Computing Lab, Kyoto University of Advanced Science (KUAS), Kyoto 615-8577, Japan.ORCID 0000-0002-2328-5016

Funding

JSPS KAKENHI 21K17670
6 · The paper itself

Abstract

The use of wearable devices for sleep apnea detection is growing, but their limited signal resolution poses challenges for accurate diagnosis. This study explores the feasibility of using SpO

Indexed as

Oxygen SaturationSleep Apnea SyndromesWearable Electronic DevicesAlgorithmsFemaleHumansMachine LearningMaleOximetryPolysomnographySignal Processing, Computer-Assistedfeature engineeringmachine learningsleep apneaSpO2wearable

Identifiers

PMID40292768
PMCPMC11944722

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.