In-Home Diagnosis of Obstructive Sleep Apnea Using Automatic Video Analysis

Abstract

Study objectives: To evaluate the diagnostic accuracy of a non-invasive technology based on image processing for the identification of obstructive sleep apnea (OSA) and its severity at patients' home.

Methods: Observational, prospective, diagnostic accuracy study to evaluate the degree of measure agreement between Sleepwise (SW), in-laboratory attended polysomnography (PSG) and a home sleep apnea test (HSAT). 38 consecutive subjects with suspected OSA referred as outpatients to the sleep unit were recruited from September 2016 to September 2017. All patients underwent in-laboratory attended PSG and image processing with SW simultaneously overnight. Subsequently, a HSAT and image processing with SW were performed simultaneously overnight at patients' home, and the 2 nights after, patients underwent only image processing with SW consecutively.

Results: In-laboratory polysomnography and SW had a Lin's concordance correlation coefficient of 0.933 and a κ of 0.930. Between HSAT and SW the Lin's concordance correlation coefficient was 0.842 and a κ of 0.571. Agreement between two consecutive nights with SW recording showed a Lin's concordance correlation coefficient of 0.923 and a κ of 0. 837.

Conclusions: SW was highly accurate for non-invasive and automatic diagnosis of OSA in outpatients compared to standard methods for OSA diagnosis either in-laboratory attended PSG or HSAT. SW proved to be a technique with repeatable and concordant results on different nights for the same patient. We conclude SW is a non-invasive, easy-to-use, portable, effective and highly accurate system for the in-home diagnosis of OSA.

Keywords: Diagnóstico de apnea obstructiva del sueño; Image processing; No invasivo; Non-invasive; Obstructive sleep apnea diagnosis; Procesamiento de imágenes.