Accelerometry-derived respiratory index estimating apnea-hypopnea index for sleep apnea screening
نویسندگان
چکیده
Sleep Apnea Syndrome (SAS) is a multimorbid chronic disease with individual and societal deleterious consequences. Polysomnography (PSG) the multi-parametric reference diagnostic tool that allows manual quantification of apnea-hypopnea index (AHI) to assess SAS severity. The burden affecting nearly one billion people worldwide explaining remains largely under-diagnosed undertreated. development an easy use automatic solution for early detection screening highly desirable. We proposed Accelerometry-Derived Respiratory (ADR) based on dual accelerometry system airflow estimation included in machine learning process. It calculated AHI thanks RUSBoosted Tree model used physiological explanatory specifically developed features. performances this method were evaluated against configuration using gold-standard PSG signals database 28 subjects. accuracy, specificity sensitivity ADR 89%, 100% 80% respectively. added value features was also demonstrated. Overnight monitoring approach provided clinically relevant estimate screening. component has real interest improving performance facilitating physician's adhesion estimation.
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_______________________________________________________________________________________________________ 1. MD. Associate Professor of Otolaryngology, Department & Research Center of Otolaryngology , Head and Neck Surgery, Hazrat Rasoul Akram Hospital, Iran University of Medical Sciences. [email protected] 2. (Corresponding author) MD. General Physician, Department & Research Center of Otolar...
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ژورنال
عنوان ژورنال: Computer Methods and Programs in Biomedicine
سال: 2021
ISSN: ['1872-7565', '0169-2607']
DOI: https://doi.org/10.1016/j.cmpb.2021.106209