Abstract: A negative pressure wound treatment (NPWT) apparatus for suction of bodily fluids using the negative pressure generated by means of manual pressing. The NPWT apparatus is made of two parts: [1] top functional part; and [2] bottom collector part. The top functional part is made of a pressing mechanism attached to a bellow enclosed within an enclosure which creates negative pressure sucking the bodily fluid from the wound. The bottom collector part is attached with the bellow through the internal one-way valve, wherein the collector collects the fluid from the bellow. Pressure levels and wound conditions are measured and transmitted to the user's smart device, in order to enhance treatment monitoring and efficacy.

Abstract: There is provided a computer-implemented device comprising a processor, a machine readable medium storing instructions, the instructions when executed by the processor for configuring the device for: receiving an airflow and volume signal from at least one airflow and volume sensor for a plurality of patients; digitizing the signal to a digital signal and segmenting the signal using a sliding window to extract a plurality of features from the digital signal comprising: peak-to-peak amplitude, root mean square, integral of the absolute values, zero-crossing rate, standard deviation of a first derivative, mean value; normalizing the plurality of extracted features; and, using the normalized plurality of extracted features and an input indicating sleep apnea severity to train a machine learning algorithm and generate a mathematical model for subsequent use in classifying airflow and volume sensed signals received for a particular patient during wakefulness as normal or sleep apnea.

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: The present invention provides a manually operated negative pressure wound treatment (NPWT) apparatus for suction of bodily fluids using the negative pressure generated by means of manual pressing. The NPWT apparatus is made of two parts: [1] top functional part; and [2] bottom collector part. The top functional part is made of a pressing mechanism attached to a bellow enclosed within an enclosure. The bellow is connected to the wound dressing using an external medical tube through a one-way check valve, wherein the negative pressure gets created within the bellows when compressed by manually pressing the mechanism. The negative pressure of the bellows sucks the bodily fluid from the wound, which promotes a new blood supply, cleaning infection, and accelerates healing dramatically. The bottom collector part is attached with the bellow through the internal one-way valve, wherein the collector collects the fluid from the bellow when the piston is pressed in the next cycle.

Abstract: There is provided a computer-implemented device comprising a processor, a machine readable medium storing instructions, the instructions when executed by the processor for configuring the device for: receiving an airflow and volume signal from at least one airflow and volume sensor for a plurality of patients; digitizing the signal to a digital signal and segmenting the signal using a sliding window to extract a plurality of features from the digital signal comprising: peak-to-peak amplitude, root mean square, integral of the absolute values, zero-crossing rate, standard deviation of a first derivative, mean value; normalizing the plurality of extracted features; and, using the normalized plurality of extracted features and an input indicating sleep apnea severity to train a machine learning algorithm and generate a mathematical model for subsequent use in classifying airflow and volume sensed signals received for a particular patient during wakefulness as normal or sleep apnea.

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.

Abstract: 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.

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. 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 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.

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: 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.

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.

Abstract: 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.

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 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.

Abstract: Disclosed herein is a mask to be worn by a subject on its face for use in respiratory monitoring and/or diagnostics. In general, the mask comprises at least one transducer responsive to sound and airflow for generating a data signal representative thereof, and a support structure shaped and configured to rest on the subject's face and thereby delineate a nose and mouth area thereof. The support structure comprises two or more outwardly projecting limbs that, upon positioning the mask, converge into a transducer supporting portion for supporting the at least one transducer at a distance from the area, thereby allowing for monitoring via the at least one transducer of both sound and airflow produced by the subject while breathing. The limbs may, in some examples, have along at least a portion thereof, an inward-facing channel defined therein for channeling toward a given transducer, air flow produced by the subject while breathing.