RESPIRATION MONITORING METHOD AND SYSTEM

• US 20130331723A1
• Filed: 01/23/2012
• Published: 12/12/2013
• Est. Priority Date: 02/22/2011
• Status: Abandoned Application

• Current Assignee: Toumaz UK Limited
• Original Assignee: Toumaz UK Limited
• Inventors: Burdett, Alison, Hernandez-Silveira, Miguel, Ang, Su-Shin
• Application Number:
  US13/977,246
• Publication Number:
  US 20130331723A1
• Time in Patent Office: Days
• US Class Current: 600/529
• CPC Class Codes: A61B 5/0004 characterised by the type of physiological signal transmitted
• CPC Class Codes: A61B 5/053 Measuring electrical impedance or conductance of a portion of the body
• CPC Class Codes: A61B 5/0809 by impedance pneumography
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/6801 specially adapted to be attached to or worn on the body surface
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts

Abstract

A method of determining a respiration rate from a signal representative of a recorded respiration episode comprises identifying two or more uncorrupted segments within the signal, the uncorrupted segments being separated by corrupted segments, identifying the longest of the uncorrupted segments or the segment with a lowest average absolute deviation (AAD) between respiration peaks or troughs, and determining a respiration rate from the longest uncorrupted segment or the segment with the lowest AAD.

Claims

1. A method of determining a respiration rate from a signal representative of a recorded respiration episode, the method comprising providing a starter pointer and an end pointer to point to a start position and an end position of the signal representative of the episode, updating the start and end pointers to identify the start and end positions of two or more uncorrupted segments within said signal, the uncorrupted segments being separated by corrupted segments, identifying the longest of the uncorrupted segments or the segment with a lowest average absolute deviation (AAD) between respiration peaks or troughs, and determining a respiration rate from the longest uncorrupted segment or the segment with the lowest AAD.

2. The method according to claim 1 further comprising the step of a user selecting whether the longest uncorrupted segment will be used to calculate the respiration rate or whether the segment with the lowest AAD will be used to calculate the respiration rate.

3. The method according to claim 1 wherein the uncorrupted segments are identified dynamically.

4. The method according to claim 1 wherein the uncorrupted segments are identified retrospectively.

5. The method according to claim 1 wherein the step of identifying the uncorrupted segments comprises checking whether a gradient and/or amplitude of the signal does not exceed a pre-determined threshold.

6. The method according to claim 1 wherein the step of identifying the uncorrupted segments comprises identifying peaks and/or troughs in the signal, obtaining intervals between adjacent peaks and/or adjacent troughs, computing changes in said intervals and determining whether such changes exceed a pre-determined threshold.

7. The method according to claim 1 wherein the step of identifying the uncorrupted segments comprises calculating a first average absolute deviation between adjacent peaks and a second average absolute deviation between adjacent troughs, combining the first and second average absolute deviations to obtain a normalised threshold and determining whether either of the first or second average absolute deviations exceeds the normalised threshold.

8. The method according to claim 7 wherein the step of combining the first and second average absolute deviations comprises multiplying the sum of the first and second average absolute deviations by a weighting factor.

9. The method according to claim 1 further comprising pre-processing the uncorrupted segments prior to determining the respiration rate.

10. The method according to claim 9 wherein the pre-processing cornprises one or more of:

(v) data centring;

(vi) gain adjustment;

(vii) passing the segments through a self-tunable filter;

(viii) passing the segments through a low and/or high pass filter.

11. The method according to claim 1 comprising the step of respiration event checking comprising one or more of:

(i) identifying peaks and/or troughs outside a noise margin window;

(ii) classifying a peak as an inhalation event only if it is preceded by an exhalation trough;

(iii) classifying a trough as an exhalation event only if it is preceded by an inhalation peak;

(iv) discarding an inhalation and/or exhalation event if it would result in a respiration rate exceeding an expected maximum;

(v) discarding an inhalation and/or exhalation event if its amplitude is less than any one of 20%, 30%, 40% or 50% of the previous inhalation/exhalation event.

12. The method according to claim 11 further comprising performing a periodicity check to determine whether the variability in intervals between two adjacent peaks and/or two adjacent troughs exceeds a pre-determined threshold.

13. The method according to claim 1 further comprising the step of validity checking comprising calculating a number of valid peaks and/or troughs detected and evaluating whether the number is greater than or equal to a pre-determined minimum required to calculate the valid respiration rate.

14. The method according to claim 1 further comprising verifying whether an average absolute deviation for an interval between adjacent valid peaks does not exceed a preset threshold and/or an average absolute deviation for an interval between adjacent valid troughs does not exceed a preset threshold.

15. The method according to claim 1 wherein the respiration rate is calculated as the mean or median respiratory rate obtained using inhalation and/or exhalation events obtained from said identified uncorrupted segment.

16. The method according to claim 1 further comprising generating an error signal when the signal representing the respiration episode does not contain at least two segments of contiguous uncorrupted data and/or when any calculated values exceed their respective thresholds.

17. A respiration monitoring system for monitoring respiration to determine a respiration rate from a signal representative of a recorded respiration episode, the system comprising:

a sensor for generating a signal representative of a recorded respiration episode; and

a processor configured for;

providing a starter pointer and an end pointer to point to a start position and an end position of the signal representative of a recorded respiration episode,

updating the start and end pointers to identify the start and end positions of two or more uncorrupted segments within said signal, the uncorrupted segments being separated by corrupted segments,

identifying the longest of the uncorrupted segments or the segment with a lowest average absolute deviation (AAD) between respiration peaks or troughs, and

determining a respiration rate from the longest uncorrupted segment or the segment with the lowest AAD.

18. The system according to claim 17 wherein the sensor comprises an impedance pneumography device configured to generate said signal.

19. The system according to claim 17 configured as a wearable wireless device.

20. The system according to claim 17 configured a low-power battery-operated disposable device.

21. A processor for a respiration monitoring system for monitoring respiration to determine a respiration rate from a signal representative of a recorded respiration episode, said processor configured for:

providing a starter pointer and an end pointer to point to a start position and an end position of the signal representative of a recorded respiration episode,

updating the start and end pointers to identify the start and end positions of two or more uncorrupted segments within said signal, the uncorrupted segments being separated by corrupted segments,

identifying the longest of the uncorrupted segments or the segment with a lowest average absolute deviation (AAD) between respiration peaks or troughs, and

determining a respiration rate from the longest uncorrupted segment or the segment with the lowest AAD.

22. (canceled)

23. (canceled)

24. (canceled)