OSA diagnosis by respiratory movement analysis using a conventional smartphone 3D camera

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Introduction: Sleepwise (SW) is a noninvasive technology that analyses patients’ video-recorded respiratory movements to transform them into a breathing signal that determines episodes of hypopnea and apnea. While SW first version processed and analysed images from an infrared external camera, the latest version uses a conventional smartphone 3D camera. Aims and objectives: The aim of this work is to compare the concordance of SW updated version in the diagnosis of OSA and its severity with a simultaneous in-laboratory polysomnography. Methods: This is a pilot diagnostic accuracy study that included 20 consecutive adults referred to the Sleep Unit of the Hospital Universitari Germans Trias i Pujol (HGTiP) for an in-laboratory polysomnography from July 2023 to January 2024. SW analysis is based on a beta version of a smartphone app installed in an iPhone 13 (Apple, Inc., Cupertino, California, USA) placed 50 cm beside the subject. For this study, we took SW automatic analysis but a manual version for analyses is available. Results: In-laboratory polysomnography and SW had a Lin’s concordance correlation coefficient of 0.884 for the AHI and a κ of 0.829 (95% CI 0.71-0.94) for the severity of OSA. The time of sleep had a Lin’s concordance correlation coefficient of 0.324. Conclusions: The latest version of SW, using video analysis of respiratory movements recorded with a conventional smartphone 3D camera, showed good correlation with simultaneous in-laboratory polysomnography. erj;64/suppl_68/PA4463/T1 T1 t1 AHI OSA severity CCC kappa 95% CI PSG-SW 0.884 0.829 (0.71-0.94)

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