Sleep apnea and respiratory anomaly detection from a wearable band and oxygen saturation.

ABSTRACT:

Objective

Sleep-related respiratory abnormalities are typically detected using polysomnography. There is a need in general medicine and critical care for a more convenient method to detect sleep apnea automatically from a simple, easy-to-wear device. The objective was to detect abnormal respiration and estimate the Apnea-Hypopnea Index (AHI) automatically with a wearable respiratory device with and without SpO₂ signals using a large (n = 412) dataset serving as ground truth.

Design

Simultaneously recorded polysomnography (PSG) and wearable respiratory effort data were used to train and evaluate models in a cross-validation fashion. Time domain and complexity features were extracted, important features were identified, and a random forest model was employed to dete

SUBMITTER: Ganglberger W 

PROVIDER: S-EPMC8854446 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature