Abstract:
Disclosed herein are breathing disorder identification, characterization and diagnosis methods, devices and systems. In general the disclosed methods, devices and systems may rely on the characterization of breath sound amplitudes, periodic breath sounds and/or aperiodic breath sounds to characterize a breathing disorder as obstructive (e.g. obstructive sleep apnea—OSA) or non-obstructive (e.g. central sleep apnea—CSA).
Abstract:
Disclosed herein are breathing disorder identification, characterization and diagnosis methods, devices and systems. A mask is also disclosed for use in respiratory monitoring, characterization and/or diagnosis. In some embodiments, breath sound data are acquired concurrently with positional data to characterize a position dependence of a subject's breathing disorder.
Abstract:
Described herein are various embodiments of a method and system for sleep detection. For example, in one embodiment, a method is described for automatically characterizing digitized breath sounds recorded from a subject over time as indicative of the subject being one of asleep and awake. This method comprises identify individual breathing cycles in a given segment of the recorded breath sounds; calculating one or more preset breathing cycle characteristics from the identified breathing cycles; evaluating a relative regularity of the calculated characteristics for the given segment; and upon the relative regularity satisfying a preset high regularity condition, outputting a sleep status indicator that the subject was likely asleep during the segment, otherwise outputting a wake indicator that the subject was likely awake during the segment.