Granted Patent B2

US 10,112,022 · App. 14/489,552 · Granted Oct 30, 2018

Abstract

Claims (48)

1. A breathing therapy machine having an optimized auto-adjust capability comprising:

a. a blower, for delivering air to a user of said device at a pressure;

b. a processor, for controlling said blower;

c. non-volatile memory, accessible by said processor, said non-volatile memory including operational programming;

d. an airflow sensor, electrically connected to said processor for gathering data regarding a volume of airflow to said patient, said operational programming producing an airflow waveform from said gathered data; and

e. a flow limitation detection module, stored in said non-volatile memory as part of said operational programming, wherein said flow limitation detection module is configured to detect a flow limitation condition by:

grouping data points sampled from an inspiration portion of the airflow waveform into a plurality of bins;

for each bin, calculating an average slope value using the data points within the bin;

computing a plurality of variance values, wherein each variance value is computed by defining a moving window that utilizes average slope values calculated for at least three of the bins; and

selecting and analyzing a lowest variance value of the plurality of variance values to determine if the flow limitation condition exists;

wherein said pressure of said air is altered based on detection of the flow limitation condition.

2. The breathing therapy machine of claim 1 wherein said airflow waveform consists of a series of breaths, each breath consisting of an inspiration portion and an expiration portion, and further wherein said flow limitation module performs, for each of said breaths, a series of functions including:

detecting a start and end of said inspiration portion of said breath and measuring a duration of said inspiration portion; and

selecting the lowest variance value and comparing to a scale to determine if the flow limitation condition is present.

3. The breathing therapy machine of claim 2 wherein said flow limitation module is further configured to perform a function of normalizing the inspiration portion prior to computing the plurality of variance values.

4. The breathing therapy machine of claim 3 wherein said normalization function comprises:

calculating an average flow signal for said inspiration portion; and

applying a gain to said inspiration portion based on a comparison of said average flow signal to an arbitrary standard flow signal.

5. The breathing therapy machine of claim 2 wherein said flow limitation module is further configured to perform a function of applying adaptive filtering to smooth said inspiration portion of said airflow waveform portion prior to computing the plurality of variance values.

6. The breathing therapy machine of claim 5 wherein said adaptive filtering function comprises calculating a moving average of said inspiration portion.

7. The breathing therapy machine of claim 6 wherein said moving average is calculated using a window size encompassing approximately 1/9 th of said inspiration portion.

8. The breathing therapy machine of claim 2 wherein said flow limitation module is further configured to perform a function of ranking and sorting said plurality of bins, each of which corresponds to the data points sampled from an inspiration portion of the airflow waveform, based on said average slope values prior to performing said variance calculations.

9. The breathing therapy machine of claim 2 wherein said function of selecting the lowest of said variance calculations and comparing to the scale to determine if a flow limitation condition is present further comprises assigning a severity of said flow limitation condition based on the lowest variance value.

10. The breathing therapy machine of claim 9 wherein said severity of said flow limitation is selected from a group consisting of none, mild, moderate and severe.

11. The breathing therapy machine of claim 1 wherein said flow limitation detection module is further configured to perform functions comprising:

calculating a ratio of said inspiration portion to said expiration portion for each breath over several breaths; and

determining if said ratio is trending toward longer inspiration times and shorter expiration times, and, if so, utilizing said trend as confirmation of the flow limitation condition.

12. The breathing therapy machine of claim 1 wherein said flow limitation detection module is further configured to perform functions comprising:

calculating a ratio of said inspiration portion to said expiration portion for each breath over several breaths; and

determining if the flow limitation condition exists only if indicated by said calculation of said variance based on the variance values and trending information associated with said ratio.

13. The breathing therapy machine of claim 1 wherein said pressure is raised if the flow limitation condition is determined to be present for at least 15 seconds in a one minute window.

14. The breathing therapy machine of claim 1 wherein said pressure is periodically raised if the flow limitation condition is determined to be present until a certain predetermined pressure is reached, at which time the flow limitation condition is ignored.

15. The breathing therapy machine of claim 2 wherein a dampening factor is applied to each variance calculation prior to the step of selecting the lowest variance value.

16. The breathing therapy machine of claim 15 wherein a polynomial having the average slope value as an input is used to dampen the variance.

17. The breathing therapy machine of claim 15 wherein said dampening factor lessens an effect of said variance values as the average slope increases.

18. A breathing therapy machine comprising:

a blower, for delivering air to a user of said device at a pressure;

a processor, for controlling said blower;

non-volatile memory, accessible by said processor, said non-volatile memory including operational programming;

an airflow sensor configured to gather airflow data indicating a volume of airflow that is provided to a patient, wherein said operational programming is configured to produce an airflow waveform based on the gathered airflow data; and

a flow limitation detection module, stored in said non-volatile memory as part of said operational programming, wherein said flow limitation detection module is configured to detect a flow limitation condition by:

grouping data points sampled from an inspiration portion of the airflow waveform into a plurality of bins;

calculating average slope values for each of the plurality of bins using the data points within the plurality of bins;

numerically ranking and sorting said plurality of bins based upon the average slopes calculated for the plurality of bins;

computing a plurality of variance values using a moving window that iterates over the plurality of bins after the plurality of bins have been numerically ranked and sorted, wherein each variance value is computed using the moving window to identify at least three consecutive bins and to compute a variance of the average slope values associated with the three consecutive bins identified in the moving window;

selecting a lowest variance value from the plurality of computed variance values; and

analyzing the lowest variance value to determine if the flow limitation condition exists;

wherein the breathing therapy machine alters said pressure of said air in response to detecting the flow limitation condition.

Assignments (6)