Determination Of A Physiological Parameter

• US 20110071366A1
• Filed: 09/13/2010
• Published: 03/24/2011
• Est. Priority Date: 09/24/2009
• Status: Active Grant

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Nellcor Puritan Bennett LLC (Medtronic Plc)
• Inventors: McKenna, Edward M.
• Granted Patent: US 8,923,945 B2
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs

Abstract

Methods and systems are provided for transmitting and receiving photon density waves to and from tissue, and processing the received waves using wavelet transforms to identify non-physiological signal components and/or identify physiological conditions. A pulse oximeter may receive the photon density waves from the tissue to generate a signal having phase and amplitude information. A phase signal may be proportional to a scattering by total particles in the tissue, and an amplitude signal may correlate to an absorption by certain particles, providing information on a ratio of different particles in the tissue. Processing the phase and amplitude signals with wavelet transforms may enable an analysis of signals with respect to time, frequency, and magnitude, and may produce various physiological data. For example, non-physiological noise components may be identified, and certain physiological conditions may be identified by processing scalograms of the original signals with patterns corresponding to certain physiological conditions.

Claims

1. A method for processing a physiological signal, comprising the acts of:

receiving a signal in response to propagation of photon density waves through tissue;

processing the signal using a wavelet transform to generate two or more multi-dimension components; and

using the two or more multi-dimensional components to distinguish physiological and non-physiological components of the signal.

2. The method, as set forth in claim 1, wherein the wavelet transform is a Morelet wavelet.

3. The method, as set forth in claim 1, wherein the two or more multi-dimension components comprise frequency and time.

4. The method, as set forth in claim 1, comprising representing the two or more multi-dimension components as a scalogram.

5. The method, as set forth in claim 4, wherein distinguishing physiological and non-physiological components comprises identifying features on the scalogram.

6. The method, as set forth in claim 1, wherein distinguishing physiological and non-physiological components comprises employing one or more image processing techniques or facial recognition technologies.

7. The method, as set forth in claim 1, wherein distinguishing physiological and non-physiological components comprises:

cross-correlating an image representation of the two or more multi-dimension components with a known pattern or signature to produce a cross-correlated image; and

determining whether the image representation substantially includes the known pattern or signature based on the cross-correlated image.

8. The method, as set forth in claim 7, wherein determining whether the image representation substantially includes the known pattern or signature is based on comparing the spectral intensity of the cross correlated image to a threshold intensity.

9. The method, as set forth in claim 1, comprising removing the non-physiological components from the signal.

10. A monitor, comprising:

a display;

a connector port capable of receiving a signal generated in response to propagation of photon density waves through tissue; and

data processing circuitry capable of applying a continuous wavelet transform to the signal, analyzing an output of the continuous wavelet transform to distinguish between physiological and non-physiological components of the signal, generating patient physiological data based on at least the physiological components of the signal, and displaying the patient physiological data on the display.

11. The monitor, as set forth in claim 10, wherein the output of the continuous wavelet transform comprises a scalogram comprising a spectral density of the signal with respect to frequency and time.

12. The monitor, as set forth in claim 10, wherein distinguishing between physiological and non-physiological components of the signal is based on whether a phase component and an amplitude component of the signal correlate.

13. The monitor, as set forth in claim 10, wherein generating patient physiological data is based on a comparison of the output with a pattern corresponding to a physiological condition.

14. The monitor, as set forth in claim 13, wherein the comparison comprises cross-correlating the output with the pattern and determining whether the cross correlation meets a threshold.

15. A monitoring system, comprising:

a sensor suitable for acquiring photon density wave data when situated on a patient; and

a monitor in communication with the sensor, wherein the monitor distinguishes between physiological and non-physiological aspects of the photon density wave data based on a continuous wavelet transformation of the photon density wave data.

16. The monitoring system of claim 15, wherein the photon density wave data comprises information relating to a total number of particles at a tissue site where the sensor is situated on the patient and information relating to a ratio of different types of particles at the tissue site.

17. The monitoring system of claim 15, wherein the monitor distinguishes between the physiological and the non-physiological aspects based substantially on whether a phase component of the photon density wave data correlates with an amplitude component of the photon density wave data.

18. The monitoring system of claim 15, wherein the monitor is configured to identify a physiological condition based on at least the physiological aspect of the photon density wave data.

19. The monitoring system of claim 18, wherein the monitor identifies the physiological condition based on a continuous wavelet transformation of the photon density wave data.

20. The monitoring system of claim 18, wherein the monitor identifies the physiological condition based on a comparison of the continuous wavelet transformation with a pattern corresponding to the physiological condition.