University Health Network

T Douglas Bradley

Hisham Alshaer

Geoffrey Roy Fernie

Ahmad Ziad Akl

Oleksandr Igorovich Levchenko

Steven Michael Pong

Steven M Pong

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&#x2014;OSA) or non-obstructive (e.g. central sleep apnea&#x2014;CSA).

Breathing disorder identification, characterization and diagnosis methods, devices and systems

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.

Method and system for sleep detection

Disclosed is a mask for use in respiratory monitoring and/or diagnostics. The mask comprises at least one transducer responsive to sound and/or airflow for generating a signal, and a support structure to rest on the subject's face. In one embodiment, the support structure comprises two or more limbs that provide a transducer support for supporting the transducer at a distance from a nose and mouth area, allowing monitoring via the transducer of sound and/or airflow produced by the subject. Also described is a mask comprising a transducer responsive to airflow for generating a signal and a support structure to rest on the subject's face and extend outwardly over a nose and mouth area to provide a transducer support supporting the transducer at a distance from a nose and mouth area of the subject's face and at a preset orientation, for monitoring via the transducer of airflow produced by the subject.

Mask and method for use in respiratory monitoring and diagnostics

Disclosed herein is a method and device for apnea and hypopnea detection. In one embodiment, a method is provided for detecting apneas and hypopneas from a digitized breath sound recording acquired from a candidate suspected of sleep apnea. The method comprises scanning an amplitude profile of the digitized breath sound recording to identify a prospect event segment; evaluating characteristics of the prospect event segment for consistency with one or more preset apnea-specific criteria; classifying the prospect event segment as representative of an apnea upon it satisfying each of the one or more apnea-specific criteria; evaluating the prospect event characteristics for consistency with one or more preset hypopnea-specific criteria distinct from the apnea-specific criteria; and classifying the prospect event segment as representative of a hypopnea upon it satisfying each of the one or more hypopnea-specific criteria.

Method and device for apnea and hypopnea detection

Disclosed herein is a method and apparatus for monitoring, identifying and determining the breathing cycle of an individual from processed acoustic signal waveform data. The breathing sounds of an individual are recorded using a microphone and digitized such that the breathing sounds may be plotted. The data is segmented and transformed to form a plurality of segments representative of a frequency spectrum. The frequency spectrum data is transformed so as to produce magnitude bins and the sum of lower magnitude bins and the sum of higher magnitude bins are determined in a sampling of segments. A Bands Ratio is determined from the sum of lower magnitude bins and the sum of higher magnitude bins in the sampling of segments. A first bands ratio is then determined within a given segment and compared to the mean bands ratio. If the first bands ratio of the given segment is greater than the mean bands ratio by at least a predetermined multiplier, the given segment is labeled as inspiration. If the first bands ratio of the given segment is less than the mean bands ratio by at least a predetermined multiplier, the given segment is labeled as expiration.

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Toronto, Canada

T Douglas Bradley