Discrimination of cheyne-stokes breathing patterns by use of oximetry signals

• US 20160120464A1
• Filed: 12/23/2015
• Published: 05/05/2016
• Est. Priority Date: 12/23/2004
• Status: Active Grant

• Current Assignee: ResMed Pty Ltd. (ResMed Incorporated)
• Original Assignee: Resmed Limited (ResMed Incorporated)
• Inventors: Armitstead, Jeffrey Peter, Lau, Chun Yui
• Granted Patent: US 10,512,429 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0826 Detecting or evaluating apnoea events A61B5/4818 takes precedence
• CPC Class Codes: A61B 5/087 Measuring breath flow
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/6819 Nose
• CPC Class Codes: A61B 5/6823 Trunk, e.g., chest, back, abdomen, hip
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/7232 involving compression of the physiological signal, e.g. to extend the signal recording period
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61M 16/00 Devices for influencing the respiratory system of patients by gas treatment, e.g. mouth-to-mouth respiration; Tracheal tubes stimulating the respiratory movement by mechanical, pneumatic or electrical means, iron lungs combined with gas breathing means A61H31/00
• CPC Class Codes: A61M 16/026 specially adapted for predicting, e.g. for determining an information representative of a flow limitation during a ventilation cycle by using a root square technique or a regression analysis
• CPC Class Codes: A61M 2230/40 Respiratory characteristics
• CPC Class Codes: G06F 18/217 Validation; Performance evaluation; Active pattern learning techniques
• CPC Class Codes: G06F 18/2411 based on the proximity to a decision surface, e.g. support vector machines
• CPC Class Codes: G06F 2218/10 by analysing the shape of a waveform, e.g. extracting parameters relating to peaks
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

Methods and apparatus provide Cheyne-Stokes respiration (“CSR”) detection based on a blood gas measurements such as oximetry. In some embodiments, a duration, such as a mean duration of contiguous periods of changing saturation or re-saturation occurring in an epoch taken from a processed oximetry signal, is determined. An occurrence of CSR may be detected from a comparison of the duration and a threshold derived to differentiate saturation changes due to CSR respiration and saturation changes due to obstructive sleep apnea. The threshold may be a discriminant function derived as a classifier by an automated training method. The discriminant function may be further implemented to characterize the epoch for CSR based on a frequency analysis of the oximetry data. Distance from the discriminant function may be utilized to generate probability values for the CSR detection.

Claims

1. A computer implemented method of detecting an occurrence of Cheyne-Stokes respiration in one or more programmed processors comprising:

accessing blood gas data representing a measured blood gas signal;

determining a duration of one or more contiguous periods of changing saturation of a blood gas from the blood gas data; and

detecting the occurrence of Cheyne-Stokes respiration from a comparison of the determined duration and a threshold derived to differentiate saturation changes due to Cheyne-Stokes respiration and saturation changes due to obstructive sleep apnea.

2. The method of claim 1 wherein the one or more contiguous periods of changing saturation comprises re-saturation periods and the measured blood gas signal comprises an oximetry signal.

3. The method of claim 2 wherein the determined duration comprises a mean period length and wherein the detecting indicates an occurrence when the mean period length exceeds the threshold.

4. The method of claim 3 wherein the threshold comprises a discriminant function.

5. The method of claim 4 wherein the detecting the occurrence further comprises determining a distance from the threshold and comparing the distance to a further threshold.

6. The method of claim 4 further comprising determining a presence of a peak in a predetermined frequency range for de-saturation and re-saturation cycles of the blood gas data and comparing the determined presence to the discriminant function.

7. The method of claim 6 further comprising processing the blood gas data to remove artifact data.

8. The method of claim 7 further comprising measuring the blood gas with an oximeter.

9. The method of claim 7 wherein the processing the blood gas data to remove artifact data comprises determining in the one or more processors a beginning and end of an motion artifact period in the blood gas data by identifying with a derivative signal of the blood gas data an initial negative spike with a first lesser threshold followed by a positive spike with a second greater threshold.

10. The method of claim 1, further comprising determining a quality indicator for determining a confidence level associated with detecting the occurrence of Cheyne-Stokes respiration.

11. The method of claim 10, wherein the processor determines the quality indicator by determining a number of samples where the measured blood gas signal drops below a predetermined percentage threshold.

12. The method of claim 11, wherein the predetermined percentage threshold is 10%.

13. The method of claim 11, wherein the quality indicator is a function of a ratio of the number of samples where the measured blood gas signal drops below the predetermined percentage threshold and a total number of samples considered.

14. An apparatus to detect an occurrence of Cheyne-Stokes breathing, the apparatus comprising:

a memory for blood gas data representing a measured blood gas signal; and

a processor coupled with the memory, the processor being configured (a) to determine a duration of one or more contiguous periods of changing saturation of a blood gas from the blood gas data and (b) to detect an occurrence of Cheyne-Stokes respiration from a comparison of the determined duration and a threshold derived to differentiate saturation changes due to Cheyne-Stokes respiration and saturation changes due to obstructive sleep apnea.

15. The apparatus of claim 14 wherein the one or more contiguous periods of changing saturation comprises re-saturation periods and the measured blood gas signal comprises an oximetery signal.

16. The apparatus of claim 15 wherein the determined duration comprises a mean period length and wherein the detecting indicates an occurrence when the mean period length exceeds the threshold.

17. The apparatus of claim 16 wherein the threshold comprises a discriminant function.

18. The apparatus of claim 17 wherein the processor is configured to detect the occurrence by further determining a distance from the discriminant function and comparing the distance to a further threshold.

19. The apparatus of claim 17 wherein the processor is further configured to determine a presence of a peak in a predetermined frequency range for de-saturation and re-saturation cycles of the blood gas data and comparing the determined presence to the discriminant function.

20. The apparatus of claim 19 wherein the processor is further configured to process the blood gas data to remove artifact data.

21. The apparatus of claim 20 further comprising an oximeter, coupled with the processor, to generate the blood gas signal.

22. The apparatus of claim 20 wherein the processor is configured to process the blood gas data to remove artifact by determining a beginning and end of a motion artifact period in the blood gas data by identifying with a derivative signal of the blood gas data an initial negative spike with a first lesser threshold followed by a positive spike with a second greater threshold.

23. The apparatus of claim 14, wherein the processor is further configured to determine a quality indicator for determining a confidence level associated with detecting the occurrence of Cheyne-Stokes respiration.

24. The apparatus of claim 23, wherein the processor determines the quality indicator by determining a number of samples where the measured blood gas signal drops below a predetermined percentage threshold.

25. The apparatus of claim 24, wherein the predetermined percentage threshold is 10%.

26. The apparatus of claim 24, wherein the quality indicator is a function of a ratio of the number of samples where the measured blood gas signal drops below the predetermined percentage threshold and a total number of samples considered.

27. An apparatus for detecting an occurrence of Cheyne-Stokes respiration comprising:

means for accessing blood gas data representing a measured blood gas signal;

means for determining a duration of one or more contiguous periods of changing saturation of a blood gas from the blood gas data; and

means for detecting the occurrence of Cheyne-Stokes respiration from a comparison of the determined duration and a threshold derived to differentiate saturation changes due to Cheyne-Stokes respiration and saturation changes due to obstructive sleep apnea.