NON-STATIONARY FEATURE RELATIONSHIP PARAMETERS FOR AWARENESS MONITORING

• US 20150208940A1
• Filed: 01/27/2015
• Published: 07/30/2015
• Est. Priority Date: 01/28/2014
• Status: Active Grant

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Covidien LP (Medtronic Plc)
• Inventors: Addison, Paul S., Watson, James N.
• Granted Patent: US 9,955,894 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/374 Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
• CPC Class Codes: A61B 5/4821 Determining level or depth of anaesthesia A61B5/1106 takes precedence
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/726 using Wavelet transforms

Abstract

Methods and systems are presented for determining physiological information in a physiological monitor. A physiological signal (e.g., an EEG signal) received from a subject is wavelet transformed and first and second related features that vary in scale over time are identified in the transformed signal. First and second coupled ridges of the respective first and second related features may also be identified in the transformed signal. A non-stationary relationship parameter is determined and is indicative of the relationship between the first and second features and/or between the first and second ridges. Physiological information, which may be indicative of a level of awareness of a subject, is determined based on the non-stationary relationship parameter. This physiological information may be used, for example, in an operating room to monitor/regulate the subject'"'"'s anesthetic state while under general anesthesia or in an intensive care unit to monitor the subject'"'"'s sedateness and administer medication accordingly.

Claims

1. A system for determining physiological information comprising:

an input configured for receiving a physiological signal from a subject; and

one or more processors configured for;

transforming the physiological signal based on a wavelet transform to generate a transformed signal that comprises at least a time component and a scale component;

identifying a first feature associated with the transformed signal that varies in scale over time;

identifying a second feature associated with the transformed signal that varies in scale over time, wherein the first feature is related to the second feature;

determining a non-stationary relationship parameter over time based on a third or higher order equation, the first feature, and the second feature, wherein the non-stationary relationship parameter is indicative of the relationship between the first feature and the second feature; and

determining physiological information based on the non-stationary relationship parameter.

2. The system of claim 1, wherein the physiological information is indicative of a level of awareness of the subject.

3. The system of claim 2, wherein:

determining a non-stationary relationship parameter over time comprises;

computing a first value of the non-stationary relationship parameter over a first period of time, and

computing a second value of the non-stationary relationship parameter over a second period of time; and

determining physiological information comprises comparing the computed first and second values of the non-stationary relationship parameter to determine a measure of coherence of the first and second features over time.

4. The system of claim 1, wherein the one or more processors are further configured for:

identifying a first ridge in the transformed signal, wherein the first feature comprises the first ridge;

identifying a second ridge in the transformed signal, wherein the second feature comprises the second ridge and wherein the first ridge and the second ridge form a coupled ridge pair; and

wherein determining the non-stationary relationship parameter over time is based on a third or higher order equation, the first ridge, and the second ridge.

5. The system of claim 4, wherein the one or more processors are further configured for identifying a band of interest in the transformed signal, and wherein identifying a first ridge is based on the band of interest.

6. The system of claim 4, wherein the one or more processors are further configured for:

determining suspected scales over a period of time based on the scale of the first feature and the scale of the second feature over the same time period, and

identifying a third ridge associated with the transformed signal that varies in scale over time based on a region containing the suspected scales.

7. The system of claim 4, wherein the one or more processors are further configured for:

identifying a plurality of ridges in the transformed signal;

identifying one or more coupled ridge pairs in the plurality of ridges, wherein each of the one or more coupled ridge pairs comprises respective first and second coupled ridges; and

determining a value of the non-stationary relationship parameter over time, for each of the one or more coupled ridge pairs, based on a third or higher order equation and the respective first and second coupled ridges.

8. The system of claim 7, wherein the one or more processors are further configured for computing a plurality of energy values, wherein each of the plurality of energy values is based on one of the plurality of ridges;

and wherein identifying a first ridge is based on the plurality of energy values.

9. The system of claim 7, wherein determining physiological information comprises:

determining a first value of the non-stationary relationship parameter based on a first coupled ridge pair of interest in the one or more coupled ridge pairs;

determining a second value of the non-stationary relationship parameter based on a second coupled ridge pair of interest in the one or more coupled ridge pairs; and

determining an awareness parameter based on a ratio of the first and second values of the non-stationary relationship parameter, wherein the awareness parameter is indicative of a depth of anesthesia of the subject.

10. The system of claim 7, wherein the one or more processors are further configured for:

ranking the one or more coupled ridge pairs based on the respective determined non-stationary relationship parameter values;

selecting one or more of the coupled ridge pairs based on the ranking; and

determining physiological information based on the selected one or more coupled ridge pairs.

11. The system of claim 10, wherein the one or more processors are further configured for generating a histogram of the one or more coupled ridge pairs and the respective determined non-stationary relationship parameter values, wherein the one or more coupled ridge pairs are ordered based on the ranking, and wherein the physiological information is determined based on the histogram.

12. The system of claim 11, wherein determining physiological information comprises:

identifying, based on the histogram, one or more coupled ridge pairs with respective determined non-stationary relationship parameter values that exceed a threshold; and

determining physiological information based on the identified one or more coupled ridge pairs.

13. The system of claim 1, wherein the one or more processors are further configured for determining a ratio of the powers from a first region and a second region of the power spectrum, wherein the power spectrum is determined based on the transformed signal, and wherein the ratio is indicative of a level of awareness of the subject.

14. The system of claim 1, wherein the physiological signal is an electroencephalogram EEG signal.

15. The system of claim 1, wherein determining a non-stationary relationship parameter comprises performing a bispectral analysis.

16. A method for determining physiological information comprising:

receiving from an input a physiological signal from a subject;

transforming, using one or more processors, the physiological signal based on a wavelet transform to generate a transformed signal that comprises at least a time component and a scale component;

identifying, using one or more processors, a first feature associated with the transformed signal that varies in scale over time;

identifying, using one or more processors, a second feature associated with the transformed signal that varies in scale over time, wherein the first feature is related to the second feature;

determining, using one or more processors, a non-stationary relationship parameter over time based on a third or higher order equation, the first feature, and the second feature, wherein the non-stationary relationship parameter is indicative of the relationship between the first feature and the second feature; and

determining, using one or more processors, physiological information based on the non-stationary relationship parameter.

17. The method of claim 16, wherein the physiological information is indicative of a level of awareness of the subject.

18. The method of claim 16, wherein:

determining a non-stationary relationship parameter over time comprises;

computing a first value of the non-stationary relationship parameter over a first period of time, and

computing a second value of the non-stationary relationship parameter over a second period of time; and

determining physiological information comprises comparing the computed first and second values of the non-stationary relationship parameter to determine a measure of coherence of the first and second features over time.

19. The method of claim 16, further comprising:

identifying, using one or more processors, a first ridge in the transformed signal, wherein the first feature comprises the first ridge;

identifying, using one or more processors, a second ridge in the transformed signal, wherein the second feature comprises the second ridge and wherein the first ridge and the second ridge form a coupled ridge pair; and

wherein determining the non-stationary relationship parameter over time is based on a third or higher order equation, the first ridge, and the second ridge.

20. The method of claim 19, further comprising identifying a band of interest in the transformed signal, and wherein identifying a first ridge is based on the band of interest.

21. The method of claim 16, further comprising:

identifying, using one or more processors, a plurality of ridges in the transformed signal;

identifying, using one or more processors, one or more coupled ridge pairs in the plurality of ridges, wherein each of the one or more coupled ridge pairs comprises respective first and second coupled ridges; and

determining, using one or more processors, a value of the non-stationary relationship parameter over time, for each of the one or more coupled ridge pairs, based on a third or higher order equation and the respective first and second coupled ridges.