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Article Dans Une Revue Computer Methods and Programs in Biomedicine Année : 2021

Accelerometry-Derived Respiratory Index estimating Apnea-Hypopnea Index for Sleep Apnea Screening

Résumé

Background and objective: Sleep Apnea Syndrome (SAS) is a multimorbid chronic disease with individual and societal deleterious consequences. Polysomnography (PSG) is the multi-parametric reference diagnostic tool that allows a manual quantification of the apnea-hypopnea index (AHI) to assess SAS severity. The burden of SAS is affecting nearly one billion people worldwide explaining that SAS remains largely under-diagnosed and undertreated. The development of an easy to use and automatic solution for early detection and screening of SAS is highly desirable. Methods: We proposed an Accelerometry-Derived Respiratory index (ADR) solution based on a dual accelerometry system for airflow estimation included in a machine learning process. It calculated the AHI thanks to a RUSBoosted Tree model and used physiological and explanatory specifically developed features. The performances of this method were evaluated against a configuration using gold-standard PSG signals on a database of 28 subjects. Results: The AHI estimation accuracy, specificity and sensitivity of the ADR index were 89%, 100% and 80% respectively. The added value of the specifically developed features was also demonstrated. Conclusion: Overnight physiological monitoring with the proposed ADR solution using a machine learning approach provided a clinically relevant estimate of AHI for SAS screening. The physiological component of the solution has a real interest for improving performance and facilitating physician's adhesion to an automatic AHI estimation.
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hal-03680408 , version 1 (13-06-2023)

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Paternité - Pas d'utilisation commerciale

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Aurélien Bricout, Julie Fontecave-Jallon, Jean Louis Pepin, P.Y. Gumery. Accelerometry-Derived Respiratory Index estimating Apnea-Hypopnea Index for Sleep Apnea Screening. Computer Methods and Programs in Biomedicine, 2021, 207, pp.106-209. ⟨10.1016/j.cmpb.2021.106209⟩. ⟨hal-03680408⟩
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