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Abstract
Overnight pulse oximetry allows the relatively non-invasive estimation of peripheral
blood haemoglobin oxygen saturations (SpO2 ), and forms part of the typical polysomnogram
(PSG) for investigation of obstructive sleep apnoea (OSA). While the raw SpO2 signal
can provide detailed information about OSA-related pathophysiology, this information
is typically summarized with simple statistics such as the oxygen desaturation index
(ODI, number of desaturations per hour). As such, this study reviews the technical
methods for quantifying OSA-related patterns in oximetry data. The technical methods
described in literature can be broadly grouped into four categories: (i) Describing
the detailed characteristics of desaturations events; (ii) Time series statistics;
(iii) Analysis of power spectral distribution (i.e. frequency domain analysis); and
(d) Non-linear analysis. These are described and illustrated with examples of oximetry
traces. The utilization of these techniques is then described in two applications.
First, the application of detailed oximetry analysis allows the accurate automated
classification of PSG-defined OSA. Second, quantifications which better characterize
the severity of desaturation events are better predictors of OSA-related epidemiological
outcomes than standard clinical metrics. Finally, methodological considerations and
further applications and opportunities are considered.