Abstract: A method for endo-phenotyping and risk stratifying obstructive sleep apnea (OSA) incudes acquiring signals associated with breathing over a period of time from a subject. In some embodiments, the signals associated with breathing are oxygen saturation signals (SpO2) that can be acquired using a SpO2 sensor. In some embodiments, the signals associated with breathing are snoring signals that can be acquired using an acoustic sensor. The method further includes determining at least one endo-phenotype of OSA using the acquired signals associated with breathing. In some embodiments, SpO2 signals can be used to determine endo-phenotypes including pharyngeal collapsibility, arousal threshold, ventilatory instability, hypoxic burden, and heart rate burden. In some embodiments, snoring signals can be used to determine endo-phenotypes including a site of airway collapse.

Abstract: A computerized method comprises statistically analyzing, using one or more processors, at least one section of a digitally recorded electroencephalography (EEG) signal that comprises an arousal segment to determine, for the arousal segment, at least one of amplitude and power at different frequencies as a function of time; selecting specified features from the results of the analysis and normalizing the selected features; and assigning, using one or more processors, an intensity scale value to the arousal segment based on the normalized selected features and a reference data set, the reference data set comprising normalized features corresponding to the normalized selected features and being generated based on a plurality of EEG signals comprising arousal segments to which intensity scale values have been assigned based on a visual inspection of the EEG signals.