System and method for automatic detection of a plurality of SP02 time series pattern types

• US 8,862,196 B2
• Filed: 05/06/2011
• Issued: 10/14/2014
• Est. Priority Date: 05/17/2001
• Status: Expired due to Term

• Current Assignee: Lawrence A. Lynn
• Original Assignee: Lawrence A. Lynn
• Inventors: Lynn, Lawrence A.
• Primary Examiner(s): WINAKUR, ERIC FRANK
• Application Number:
  US13/102,307
• Publication Number:
  US 20110208539A1
• Time in Patent Office: 1,257 Days
• Field of Search: 600/300, 600/310, 600/323, 600/324, 600/484, 600/529, 600/533
• US Class Current: 600/323
• CPC Class Codes: A61B 5/00 Measuring for diagnostic purposes radiation diagnosis A61B6/00; diagnosis by ultrasonic, sonic or infrasonic waves A61B8/00; Identification of persons
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/0836 Measuring rate of CO2 production
• CPC Class Codes: A61B 5/087 Measuring breath flow
• CPC Class Codes: A61B 5/0871 Peak expiratory flowmeters
• CPC Class Codes: A61B 5/145 Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissuemeasuring of blood pressure or blood flow A61B5/02; non-radiation detecting or locating of foreign bodies in blood A61B5/06
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61B 7/003 Detecting lung or respiration noise
• CPC Class Codes: A61M 16/0051 with alarm devices
• 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 16/085 Gas sampling
• CPC Class Codes: A61M 16/0858 Pressure sampling ports
• CPC Class Codes: A61M 2016/0027 pressure meter
• CPC Class Codes: A61M 2016/0042 : in the expiratory circuit
• CPC Class Codes: A61M 2205/50 : with microprocessors or computers
• CPC Class Codes: A61M 2205/502 : User interfaces, e.g. screens or keyboards
• CPC Class Codes: A61M 2205/8206 : battery-operated
• CPC Class Codes: A61M 2230/205 : partial oxygen pressure (P-O2)
• CPC Class Codes: A61M 2230/432 : partial CO2 pressure (P-CO2)
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/70 : for mining of medical data, e.g. analysing previous cases of other patients

Abstract

The disclosed embodiments relate to a patient monitor for evaluating a patient. The patient monitor may comprise a sensor that is adapted to detect a sound associated with breathing of the patient and to produce a first output indicative of the sound, an oximeter that is adapted to receive an input from the patient and to produce a second output indicative of oxygen saturation of blood of the patient, and a processor adapted to receive at least the first output and the second output and to correlate the first output with the second output.

Claims

1. A programmed method applied by a processor for processing data and for the real-time or near real-time detection of at least one occurrence of an incomplete arousal response to an apnea, hypopnea or hypoventilation, comprising:

the processor accessing data representative of a time series of at least one component of a parameter, detecting a reciprocation comprising a first variation in the data, the first variation being induced by an apnea, hypopnea or hypoventilation, the first variation having a first beginning value, a first end value and a first amplitude along the time series;

the reciprocation further comprising a second variation in the data, the second variation being induced by an arousal responsive to the apnea, hypopnea or hypoventilation, the second variation having a second beginning value, a second end value and a second amplitude along the time series, the first variation occurring in a direction opposite the direction of the second variation;

comparing at least one of the first beginning value and the first amplitude to at least one of the second end value and the second amplitude; and

detecting an incomplete reciprocation responsive to the comparing of the at least one of the first beginning value and the first amplitude to the at least one of the second end value and the second amplitude when the comparing indicates that the second amplitude is less than the first amplitude or the second end value is less than the first beginning value.

2. The method recited in claim 1, wherein at least the first variation comprises a defection event.

3. The method recited in claim 1, wherein at least the first variation comprises a trend event.

4. The method recited in claim 1, wherein at least the first variation comprises a rise.

5. The method recited in claim 1, wherein at least the first variation comprises a fall.

6. The method recited in claim 1, wherein the first variation comprises a rise and the second variation comprises a fall.

7. The method recited in claim 1, wherein the parameter comprises arterial oxygen saturation.

8. The method recited in claim 7, comprising deriving the arterial oxygen saturation data from a pulse oximeter.

9. The method recited in claim 1, wherein the parameter comprises carbon dioxide.

10. The method recited in claim 1, wherein the parameter comprises minute ventilation.

11. A programmed method applied by a processor for processing data and for the real-time or near real-time detection of at least one occurrence of an incomplete arousal response to an apnea, hypopnea or hypoventilation, comprising:

accessing data representative of a plurality of time series, each of the plurality of time series corresponding to at least one component of a parameter;

detecting a reciprocation comprising a first variation in a subset of the data that corresponds to a first one of the plurality of time series, the first variation induced by an apnea, hypopnea or hypoventilation, the first variation having a first beginning value, a first end value and a first amplitude along the first one of the plurality of time series;

the reciprocation further comprising a second variation induced by an arousal responsive to the apnea, hypopnea or hypoventilation, the second variation being in a subset of the data that corresponds to a second one of the plurality of time series, the second variation having a second beginning value, a second end value and a second amplitude along the second one of the plurality of time series, the first variation occurring in a direction opposite the direction of the second variation;

comparing at least one of the first beginning value and the first amplitude to at least one of the second end value and the second amplitude; and

detecting an incomplete reciprocation responsive to the comparing of the at least one of the first beginning value and the first amplitude to the at least one of the second end value and the second amplitude when the comparing indicates that the second amplitude is less than the first amplitude or the second end value is less than the first beginning value.

12. The method recited in claim 11, wherein at least the first variation comprises a defection event.

13. The method recited in claim 11, wherein at least the first variation comprises a trend event.

14. The method recited in claim 11, wherein at least the first variation comprises a rise.

15. The method recited in claim 11, wherein at least the first variation comprises a fall.

16. The method recited. in claim 11, wherein the first variation comprises a rise and the second variation comprises a fall.

17. The method recited in claim 11, wherein the parameter represented by the first time series comprises arterial oxygen saturation.

18. The method recited in claim 17, comprising deriving the arterial oxygen saturation data from a pulse oximeter.

19. The method recited in claim 17, wherein the parameter represented by the second time series comprises minute ventilation.

20. The method recited in claim 11, wherein the parameter represented by the first time series comprises carbon dioxide.

21. A data processing system for the real-time or near real-time detection of at least one occurrence of an incomplete arousal response to an apnea, hypopnea or hypoventilation, comprising:

a memory that is adapted to store data representative of a time series of at least one component of a parameter; and

a processor that is adapted to;

detect a reciprocation comprising a first variation in the data, the first variation being induced by an apnea, hypopnea or hypoventilation, the first variation having a first beginning value, a first end value and a first amplitude along the time series;

the reciprocation further comprising a second variation in the data, the second variation being induced by an arousal responsive to the apnea, hypopnea or hypoventilation, the second variation having a second beginning value, a second end value and a second amplitude along the time series, the first variation occurring in a direction opposite the direction of the second variation;

compare at least one of the first beginning value and the first amplitude to at least one of the second end value and the second amplitude; and

detect an incomplete reciprocation responsive to the comparing of the at least one of the first beginning value and the first amplitude to the at least one of the second end value and the second amplitude when the comparing indicates that the second amplitude is less than the first amplitude or the second end value is less than the first beginning value.

22. The data processing system recited in claim 21, wherein the parameter comprises arterial oxygen saturation.

23. The data processing system recited in claim 22, wherein the arterial oxygen saturation is derived from a pulse oximeter.

24. The data processing system recited in claim 21, wherein the parameter comprises carbon dioxide.

25. The data processing system recited in claim 21, wherein the parameter comprises minute ventilation.

26. A data processing system for the real-time or near real-time detection of at least one occurrence of an incomplete arousal response to an apnea, hypopnea or hypoventilation, comprising:

means for storing data representative of a time series of at least one component of a parameter; and

means for detecting a reciprocation comprising a first variation in the data, the first variation being induced by an apnea, hypopnea or hypoventilation, the first variation having a first beginning value, a first end value and a first amplitude along the time series, the reciprocation further comprising a second variation in the data, the second variation being induced by an arousal responsive to the apnea, hypopnea or hypoventilation, the second variation having a second beginning value, a second end value and a second amplitude along the time series, the first variation occurring in a direction opposite the direction of the second variation, comparing at least one of the first beginning value and the first amplitude to at least one of the second end value and the second amplitude, and detecting an incomplete reciprocation responsive to the comparing of the at least one of the first beginning value and the first amplitude to the at least one of the second end value and the second amplitude when the comparing indicates that the second amplitude is less than the first amplitude or the second end value is less than the first beginning value.

27. The data processing system recited in claim 26, wherein the parameter comprises arterial oxygen saturation.

28. The data processing system recited in claim 27, wherein the arterial oxygen saturation is derived from a pulse oximeter.

29. The data processing system recited in claim 26, wherein the parameter comprises carbon dioxide.

30. A tangible machine-readable medium comprising:

code adapted to access data representative of a time series of at least one component of a parameter;

code adapted to detect a reciprocation comprising a first variation in the data, the first variation being induced by an apnea, hypopnea or hypoventilation, the first variation having a first beginning value, a first end value and a first amplitude along the time series, the reciprocation further comprising a second variation in the data, the second variation being induced by an arousal responsive to the apnea, hypopnea or hypoventilation, the second variation having a second beginning value, a second end value and a second amplitude along the time series, the first variation occurring in a direction opposite the direction of the second variation;

code adapted to compare at least one of the first beginning value and the first amplitude to at least one of the second end value and the second amplitude; and

code adapted to detect an incomplete reciprocation responsive to the comparing of the at least one of the first beginning value and the first amplitude to the at least one of the second end value and the second amplitude when the comparing indicates that the second amplitude is less than the first amplitude or the second end value is less than the first beginning value.

31. A programmed method applied by a processor for processing data, comprising:

accessing data representative of a time series of at least one component of a parameter; and

searching for a subset of the data that is representative of an incomplete reciprocation induced by an incomplete arousal response to an apnea, a hypopnea or to hypoventilation, wherein the incomplete reciprocation is comprised of a first variation in a first direction, the first variation defining a first amplitude, and a second variation in a second direction opposite the first direction, the second variation defining a second amplitude, the incomplete reciprocation indicated when the second amplitude of the second variation being less than the first amplitude of the first variation.

32. The method recited in claim 31, wherein the parameter comprises arterial oxygen saturation.

33. The method recited in claim 32, comprising deriving the arterial oxygen saturation data from a pulse oximeter.

34. The method recited in claim 33, comprising analyzing the incomplete reciprocation to determine a severity of the incomplete reciprocation.

35. The method of claim 34 comprising determining a severity index based on the severity of the incomplete reciprocation.

36. The method of claim 34 comprising outputting an indication of arousal failure based on the incomplete reciprocation.

37. The method recited in claim 33, comprising adjusting a narcotic dose based on the act of detecting.

38. The method recited in claim 33, comprising, sending a signal to a narcotic infusion pump, and adjusting the narcotic infusion pump to reduce or stop the infusion of narcotic by the pump, based on the act of detecting.

39. The method recited in claim 33, comprising adjusting a positive airway pressure device based on the act of detecting.

40. The method recited in claim 33, comprising adjusting a drug infusion pump based on the act of detecting.

41. The method recited in claim 33, comprising providing an alarm responsive to the act of detecting.

42. The method recited in claim 32, comprising detecting a magnitude ratio associated with the incomplete reciprocation.

43. The method recited in claim 42, comprising detecting a morphology associated with the incomplete reciprocation.

44. The method recited in claim 32, wherein the parameter comprises minute ventilation.

45. The method recited in claim 31, wherein the parameter comprises carbon dioxide.

46. A method for processing data, comprising:

accessing data representative of a time series of at least one component of a parameter; and

defining a plurality of programmatic objects that each represent a segment of the time series, the time series comprising a plurality of reciprocations, detecting an object comprising a first component of a reciprocation defining a first amplitude and a beginning value, detecting an object comprising a second component of a reciprocation defining a second amplitude and an end value, comparing the first object to the second object to detect an incomplete reciprocation when the comparing indicates that the second amplitude is less than the first amplitude or the end value of the second component is less than the beginning value of the first component.