000128117 001__ 128117
000128117 005__ 20250923084409.0
000128117 0247_ $$2doi$$a10.1109/JBHI.2023.3331947
000128117 0248_ $$2sideral$$a135343
000128117 037__ $$aART-2024-135343
000128117 041__ $$aeng
000128117 100__ $$aCajal, Diego$$uUniversidad de Zaragoza
000128117 245__ $$aObstructive Sleep Apnea Screening by Joint Saturation Signal Analysis and PPG-derived Pulse Rate Oscillations
000128117 260__ $$c2024
000128117 5060_ $$aAccess copy available to the general public$$fUnrestricted
000128117 5203_ $$aObstructive sleep apnea (OSA) is a high-prevalence disease in the general population, often underdiagnosed. The gold standard in clinical practice for its diagnosis and severity assessment is the polysomnography, although in-home approaches have been proposed in recent years to overcome its limitations. Today's ubiquitously presence of wearables may become a powerful screening tool in the general population and pulse-oximetry-based techniques could be used for early OSA diagnosis. In this work, the peripheral oxygen saturation together with the pulse-to-pulse interval (PPI) series derived from photoplethysmography (PPG) are used as inputs for OSA diagnosis. Different models are trained to classify between normal and abnormal breathing segments (binary decision), and between normal, apneic and hypopneic segments (multiclass decision). The models obtained 86.27% and 73.07% accuracy for the binary and multiclass segment classification, respectively. A novel index, the cyclic variation of the heart rate index (CVHRI), derived from PPI's spectrum, is computed on the segments containing disturbed breathing, representing the frequency of the events. CVHRI showed strong Pearson's correlation (r) with the apnea-hypopnea index (AHI) both after binary (r=0.94, p < 0.001) and multiclass (r=0.91, p < 0.001) segment classification. In addition, CVHRI has been used to stratify subjects with AHI higher/lower than a threshold of 5 and 15, resulting in 77.27% and 79.55% accuracy, respectively. In conclusion, patient stratification based on the combination of oxygen saturation and PPI analysis, with the addition of CVHRI, is a suitable, wearable friendly and low-cost tool for OSA screening at home.
000128117 536__ $$9info:eu-repo/grantAgreement/ES/MCIU-AEI-FEDER/PID2021-126734OB-C21$$9info:eu-repo/grantAgreement/ES/MICIU-FEDER/PDC2021-120775-I00$$9info:eu-repo/grantAgreement/ES/MICIU-FEDER/PID2019-104881RB-I00
000128117 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000128117 590__ $$a6.8$$b2024
000128117 592__ $$a1.649$$b2024
000128117 591__ $$aCOMPUTER SCIENCE, INFORMATION SYSTEMS$$b21 / 258 = 0.081$$c2024$$dQ1$$eT1
000128117 591__ $$aMATHEMATICAL & COMPUTATIONAL BIOLOGY$$b3 / 67 = 0.045$$c2024$$dQ1$$eT1
000128117 591__ $$aMEDICAL INFORMATICS$$b6 / 48 = 0.125$$c2024$$dQ1$$eT1
000128117 591__ $$aCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS$$b23 / 175 = 0.131$$c2024$$dQ1$$eT1
000128117 593__ $$aElectrical and Electronic Engineering$$c2024$$dQ1
000128117 593__ $$aBiotechnology$$c2024$$dQ1
000128117 593__ $$aHealth Information Management$$c2024$$dQ1
000128117 593__ $$aHealth Informatics$$c2024$$dQ1
000128117 593__ $$aComputer Science Applications$$c2024$$dQ1
000128117 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000128117 700__ $$0(orcid)0000-0001-7285-0715$$aGil, Eduardo$$uUniversidad de Zaragoza
000128117 700__ $$0(orcid)0000-0003-3434-9254$$aLaguna, Pablo$$uUniversidad de Zaragoza
000128117 700__ $$aVaron, Carolina
000128117 700__ $$aTestelmans, Dries
000128117 700__ $$aBuyse, Bertien
000128117 700__ $$aJensen, Chris
000128117 700__ $$aHoare, Rohan
000128117 700__ $$aBailón, Raquel
000128117 700__ $$0(orcid)0000-0001-8742-0072$$aLázaro, Jesús$$uUniversidad de Zaragoza
000128117 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát.
000128117 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac.
000128117 773__ $$g28, 1 (2024), 37948138 [11 pp.]$$pIEEE j. biomed. health inform.$$tIEEE journal of biomedical and health informatics$$x2168-2194
000128117 8564_ $$s1105377$$uhttps://zaguan.unizar.es/record/128117/files/texto_completo.pdf$$yPostprint
000128117 8564_ $$s3578744$$uhttps://zaguan.unizar.es/record/128117/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000128117 909CO $$ooai:zaguan.unizar.es:128117$$particulos$$pdriver
000128117 951__ $$a2025-09-22-14:29:23
000128117 980__ $$aARTICLE