Obstructive Sleep Apnea Screening by Joint Saturation Signal Analysis and PPG-derived Pulse Rate Oscillations

Cajal, Diego (Universidad de Zaragoza) ; Gil, Eduardo (Universidad de Zaragoza) ; Laguna, Pablo (Universidad de Zaragoza) ; Varon, Carolina ; Testelmans, Dries ; Buyse, Bertien ; Jensen, Chris ; Hoare, Rohan ; Bailón, Raquel ; Lázaro, Jesús (Universidad de Zaragoza)

Resumen: Obstructive 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.

Idioma: Inglés

DOI: 10.1109/JBHI.2023.3331947

Año: 2024

Publicado en: IEEE journal of biomedical and health informatics 28, 1 (2024), 37948138 [11 pp.]
ISSN: 2168-2194

Factor impacto JCR: 6.8 (2024)

Categ. JCR: COMPUTER SCIENCE, INFORMATION SYSTEMS rank: 21 / 258 = 0.081 (2024) - Q1 - T1
Categ. JCR: MATHEMATICAL & COMPUTATIONAL BIOLOGY rank: 3 / 67 = 0.045 (2024) - Q1 - T1
Categ. JCR: MEDICAL INFORMATICS rank: 6 / 48 = 0.125 (2024) - Q1 - T1
Categ. JCR: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS rank: 23 / 175 = 0.131 (2024) - Q1 - T1

Factor impacto SCIMAGO: 1.649 - Electrical and Electronic Engineering (Q1) - Biotechnology (Q1) - Health Information Management (Q1) - Health Informatics (Q1) - Computer Science Applications (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MCIU-AEI-FEDER/PID2021-126734OB-C21
Financiación: info:eu-repo/grantAgreement/ES/MICIU-FEDER/PDC2021-120775-I00
Financiación: info:eu-repo/grantAgreement/ES/MICIU-FEDER/PID2019-104881RB-I00

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Ingen.Sistemas y Automát. (Dpto. Informát.Ingenie.Sistms.)
Área (Departamento): Área Teoría Señal y Comunicac. (Dpto. Ingeniería Electrón.Com.)