Evidence map›Paper›PMID 41712139›Full record

ArticleSleep & breathing = Schlaf & Atmung2026

Towards automatic home screening of obstructive sleep apnea using combined features from pulse wave amplitude, pulse-to-pulse interval and oxygen desaturation.

Wanwara Thuptimdang, Krongthong Tawaranurak, Pattaraporn Panyarath, Wandee Rakim, Katinee Wae-Asae, Michael C K Khoo

Abstract read
In one paragraph

Article in Sleep & breathing = Schlaf & Atmung, 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

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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

6 authors.

Wanwara ThuptimdangInstitute of Biomedical Engineering, Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand. wanwara.t@psu.ac.th.ORCID 0009-0000-3769-5967
Krongthong TawaranurakDepartment of Otolaryngology Head and Neck Surgery, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand.
Pattaraporn PanyarathDivision of Respiratory and Respiratory Critical Care Medicine, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand.
Wandee RakimSongklanagarind Hospital Sleep Center, Prince of Songkla University, Hat Yai, Songkhla, Thailand.
Katinee Wae-AsaeSongklanagarind Hospital Sleep Center, Prince of Songkla University, Hat Yai, Songkhla, Thailand.
Michael C K KhooDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA.

Funding

National Science, Research and Innovation Fund (NSRF) and Prince of Songkla University MED6701239S
6 · The paper itself

Abstract

purposeAutomatic home OSA screening with pulse oximeters often relies on oxygen saturation (SpO2), which may miss hypopneas associated with arousals. Photoplethysmography (PPG) from pulse oximeters can be processed to extract pulse wave amplitude (PWA) and pulse-to-pulse interval (PPI) which reflect autonomic activation during arousals. However, the role of PWA in automated OSA screening remains unexplored. This study evaluated the added value of PWA for detecting OSA segments, and estimating AHI compared with SpO2 and PPI.

methodFrom 90 PSG recordings, PWA and PPI were derived from finger PPG. We extracted statistical PWA features to capture amplitude drops, and spectral powers to represent pulse amplitude variability. PPI features included statistics and heart rate variability measures. Support vector machine classifiers with different combinations of PWA, PPI, and SpO2 features were trained to detect 60-second segments with apnea or hypopnea. Performance was assessed at both per-segment and per-subject levels for identifying AHI ≥ 15.

resultsAdding PWA to SpO2 improved sensitivity for arousal-related OSA segments from 61.6% to 65.2% and increased per-subject sensitivity from 61.4% to 64.9%. Adding PPI to SpO2 improved per-segment sensitivity for arousal-related OSA segments to 73.3% and increased per-subject sensitivity to 77.2%. Combining PWA with PPI achieved the highest sensitivity for arousal-related segments (77.1%), and when both were added to SpO2, per-subject sensitivity for detecting AHI ≥ 15 reached 80.7%.

conclusionBoth PWA and PPI improved detection of arousal-related segments and contributed to detecting subjects with AHI ≥ 15. However, PPI consistently outperformed PWA. SpO2 remained particularly important for identifying subjects with AHI < 15.

Indexed as

OximetryOxygen SaturationPhotoplethysmographyPulse Wave AnalysisSleep Apnea, ObstructiveAdultArousalFemaleHeart RateHumansMaleMiddle AgedPolysomnographySensitivity and SpecificityHeart rate variabilityObstructive sleep apneaOxygen saturationPhotoplethysmographyPulse wave amplitudeRespiratory arousal

Identifiers

PMID41712139
PMCPMC12920278

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LicenceCC BY
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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.