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Signal processing apparatus    

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United States Patent5632272   
Link to this pagehttp://www.wikipatents.com/5632272.html
Inventor(s)Diab; Mohamed K. (Laguna Niguel, CA); Kiani-Azarbayjany; Esmaiel (Laguna Niguel, CA); Elfadel; Ibrahim M. (Laguna Niguel, CA); McCarthy; Rex J. (Mission Viejo, CA); Weber; Walter M. (Los Angeles, CA); Smith; Robert A. (Corona, CA)
AbstractThe present invention involves method and apparatus for analyzing two measured signals that are modeled as containing primary and secondary portions. Coefficients relate the two signals according to a model defined in accordance with the present invention. In one embodiment, the present invention involves utilizing a transformation which evaluates a plurality of possible signal coefficients in order to find appropriate coefficients. Alternatively, the present invention involves using statistical functions or Fourier transform and windowing techniques to determine the coefficients relating to two measured signals. Use of this invention is described in particular detail with respect to blood oximetry measurements.
   














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Drawing from US Patent 5632272
Signal processing apparatus - US Patent 5632272 Drawing
Signal processing apparatus
Inventor     Diab; Mohamed K. (Laguna Niguel, CA); Kiani-Azarbayjany; Esmaiel (Laguna Niguel, CA); Elfadel; Ibrahim M. (Laguna Niguel, CA); McCarthy; Rex J. (Mission Viejo, CA); Weber; Walter M. (Los Angeles, CA); Smith; Robert A. (Corona, CA)
Owner/Assignee     Masimo Corporation (Mission Viejo, CA)
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Publication Date     May 27, 1997
Application Number     08/320,154
PAIR File History     Application Data   Transaction History
Image File Wrapper   Patent Term   Fees
Litigation
Filing Date     October 7, 1994
US Classification     600/323 600/479
Int'l Classification     A61B 005/00
Examiner     Sykes; Angela D.
Assistant Examiner    
Attorney/Law Firm     Knobbe, Martens, Olson & Bear, LLP.
Address
Parent Case     Reference to Prior Related Application This is a continuation-in-part application of U.S. patent application Ser. No. 08/132,812 filed Oct. 6, 1993, and entitled "Signal Processing Apparatus" now U.S. Pat. No. 5,490,505 and a continuation-in-part application of U.S. patent application Ser. No. 08/249,690 filed May 26, 1994 entitled "Signal Processing Apparatus and Method", now U. S. Pat. No. 5,482,036 which is a continuation of U.S. patent application Ser. No. 07/666,060 filed Mar. 7, 1991, now abandoned.
Priority Data    
USPTO Field of Search     128/633 128/634 128/633 128/634 128/672 128/633 128/634 128/716 356/39 356/40 356/41
Patent Tags     signal processing
   
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What is claimed is:

1. In a signal processor for processing at least two measured signals S.sub.1 and S.sub.2 each containing a primary signal portion s and a secondary signal portion n, said signals S.sub.1 and S.sub.2 being in accordance with the following relationship:

S.sub.1 =s.sub.1 +n.sub.1

S.sub.2 =s.sub.2 +n.sub.2

where s.sub.1 and s.sub.2, and n.sub.1 and n.sub.2 are related by:

s.sub.1 =r.sub.a s.sub.2 and n.sub.1 =r.sub.v n.sub.2

and where r.sub.a and r.sub.v are coefficients,

a method comprising the steps of:

determining a value for the coefficient r.sub.a which minimizes correlation between s.sub.1 and n.sub.1 ;

calculating the blood oxygen saturation from said value of r.sub.a ; and

displaying the blood oxygen saturation on a display.

2. In a signal processor for processing at least first and second measured signals S.sub.1 and S.sub.2 each containing a primary signal portion s and a secondary signal portion n, said signals S.sub.1 and S.sub.2 being in accordance with the following relationship:

S.sub.1 =s.sub.1 +n.sub.1

S.sub.2 =s.sub.2 +n.sub.2

where s.sub.1 and s.sub.2, and n.sub.1 and n.sub.2 are related by:

s.sub.1 =r.sub.a s.sub.2 and n.sub.1 =r.sub.v n.sub.2

and where r.sub.a and r.sub.v are coefficients,

a method comprising the steps of:

determining a value for the coefficient r.sub.a which minimizes correlation between s.sub.1 and n.sub.1 ; and

processing at least one of the first and second signals using the determined value for r.sub.a to significantly reduce n from at least one of the first or second measured signal to form a clean signal.

3. The method of claim 2, further comprising the step of displaying the resulting clean signal on a display.

4. The method of claim 2, wherein said first and second signals are physiological signals, said method further comprising the step of processing said clean signal to determine a physiological parameter from said first and second measured signals.

5. The method of claim 4, wherein said physiological parameter is arterial oxygen saturation.

6. The method of claim 4, wherein said physiological parameter is an ECG signal.

7. The method of claim 2, wherein the primary signal portion of said measured signals is indicative of a heart plethysmograph, said method further comprising the step of calculating the pulse rate.

8. A physiological monitor comprising:

a first input configured to receive a first measured signal S.sub.1 having a primary portion, s.sub.1, and a secondary portion n.sub.1 ;

a second input configured to received a second measured signal S.sub.2 having a primary portion s.sub.2 and a secondary portion n.sub.2, said first and said second measured signals S.sub.1 and S.sub.2 being in accordance with the following relationship:

S.sub.1 =s.sub.1 +n.sub.1

S.sub.2 =s.sub.2 +n.sub.2

where s.sub.1 and s.sub.2, and n.sub.1 and n.sub.2 are related by:

s.sub.1 =r.sub.a s.sub.2 and n.sub.1 =r.sub.v n.sub.2

and where r.sub.a and r.sub.v are coefficients;

a transform module responsive to said first and said second measured signals and responsive to a plurality of possible values for r.sub.a to provide at least one power curve as an output;

an extremum calculation module responsive to said at least one power curve to select a value for r.sub.a which minimizes the correlation between s and n, and to calculate from said value for r.sub.a a corresponding saturation value as an output; and

a display module responsive to the saturation value output of said extremum calculation module to display said saturation value.

9. In a signal processor for processing at least firs and second measured signals, each containing a primary signal portion and a secondary signal portion, said first and second signals substantially adhering to a predefined signal model, a method comprising the steps of:

sampling said first and second signals over a period to obtain a first series of data points representing said first signal over said period and a second series of data points representing said second signal over said period;

transforming said first series of data points into a first transformed series of points having at least a frequency component and a magnitude component and transforming said second series of data points into a second transformed series of points having at least a frequency component and a magnitude component;

comparing said first and second transformed series of points to obtain a third series of comparison values having a magnitude component and at least a frequency component;

selecting at least one of said comparison values that has a magnitude within a selected threshold; and

from said selected at least one comparison value, determining a resulting value consistent with the predefined signal model.

10. The method of claim 9, wherein said step of comparing comprises determining a series of ratios on a point-by point basis of the first transformed series of points to said second transformed series of points, and wherein said step of selecting at least one of said comparison values comprises the step of selecting the lower of the ratios.

11. The method of claim 10, wherein said step of determining a resulting value comprises calculating a blood oxygen saturation from the selected lower of the ratios.

12. The method of claim 9, wherein said resulting value is blood oxygen saturation.

13. The method of claim 9, wherein said resulting value is pulse rate.

14. In a signal processor for processing at least first and second measured signals, each containing a primary signal portion and a secondary signal portion, said first and second signals substantially adhering to a signal model for blood constituent saturation, a method comprising the steps of:

sampling said first and second signals over a period to obtain a first series of data points representing said first signal over said period and a second series of data points representing said second signal over said period;

transforming said first and second series of data points from time domain to frequency domain to obtain a first transformed series of points and a second transformed series of points, said first and second transformed series of points having a magnitude component and at least a frequency component;

determining a series of ratios of magnitudes with respect to frequency of ones of said first transformed series of points to ones of said second transformed series of points;

selecting at least one of the ratios from said series of ratios that has a magnitude within a selected threshold; and

from said selected at least one of the ratios, determining a resulting value consistent with the signal model.

15. The method of claim 14, wherein said ratios correspond to blood oxygen saturation, said step of selecting at least one of said ratios comprises selecting at least one of the ratios corresponding to the higher values of blood oxygen saturation.

16. The method of claim 15, wherein said step of determining a resulting value comprises calculating the blood oxygen saturation from the selected at least one of the ratios.

17. The method of claim 16, further comprising the steps of:

combining with a window function at least one of said first transformed series of points or said second transformed series of points with said resulting value; and

performing a spectrum analysis on the combination to obtain the pulse rate.

18. The method of claim 16, wherein said resulting value is blood oxygen saturation.

19. The method of claim 16, further comprising the steps of:

using a window function, combining at least one of said first transformed series of points or said second transformed series of points with said resulting value; and

performing an inverse window function to obtain a plethysmographic waveform.

20. In a signal processor for processing at least first and second measured signals, each containing a primary signal portion and a secondary signal portion, said first and second signals substantially adhering to a signal model, a method comprising the steps of:

sampling said first and second signals over a period to obtain a first series of data points representing said first signal over said period and a second series of data points representing said second signal over said period;

performing a fast saturation transform with said first and second series of data points to obtain a series of transformed data points in said frequency domain;

determining a selected saturation value from said series of transformed data points.

21. The method of claim 20, wherein said selected saturation value is arterial blood oxygen saturation.

22. The method of claim 20, wherein said selected saturation value is venous blood oxygen saturation.

23. The method of claim 20, wherein said step of performing said fast saturation transform comprises calculating first and second pluralities of intermediary transformed points from said first and second series of data points, said method further comprising the step of determining a pulse rate from said selected saturation value and from said first plurality of intermediary transformed points.
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BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to the field of signal processing. More specifically, the present invention relates to the processing of measured signals, containing a primary signal portion and a secondary signal portion, for the removal or derivation of either the primary or secondary signal portion when little is known about either of these components. More particularly, the present invention relates to modeling the measured signals in a novel way which facilitates minimizing the correlation between the primary signal portion and the secondary signal portion in order to produce a primary and/or secondary signal. The present invention is especially useful for physiological monitoring systems including blood oxygen saturation systems.

2. Description of the Related Art

Signal processors are typically employed to remove or derive either the primary or secondary signal portion from a composite measured signal including a primary signal portion and a secondary signal portion. For example, a composite signal may contain noise and desirable portions. If the secondary signal portion occupies a different frequency spectrum than the primary signal portion, then conventional filtering techniques such as low pass, band pass, and high pass filtering are available to remove or derive either the primary or the secondary signal portion from the total signal. Fixed single or multiple notch filters could also be employed if the primary and/or secondary signal portion(s) exist at a fixed frequency(s).

It is often the case that an overlap in frequency spectrum between the primary and secondary signal portions exists. Complicating matters further, the statistical properties of one or both of the primary and secondary signal portions change with time. In such cases, conventional filtering techniques are ineffective in extracting either the primary or secondary signal. If, however, a description of either the primary or secondary signal portion can be derived, correlation canceling, such as adaptive noise canceling, can be employed to remove either the primary or secondary signal portion of the signal isolating the other portion. In other words, given sufficient information about one of the signal portions,that signal portion can be extracted.

Conventional correlation cancelers, such as adaptive noise cancelers, dynamically change their transfer function to adapt to and remove portions of a composite signal. However, correlation cancelers require either a secondary reference or a primary reference which correlates to either the secondary signal portion only or the primary signal portion only. For instance, for a measured signal containing noise and desirable signal, the noise can be removed with a correlation canceler if a noise reference is available. This is often the case. Although the amplitude of the reference signals are not necessarily the same as the amplitude of the corresponding primary or secondary signal portions, they have a frequency spectrum which is similar to that of the primary or secondary signal portions.

In many cases, nothing or very little is known about the secondary and/or primary signal portions. One area where measured signals comprising a primary signal portion and a secondary signal portion about which no information can easily be determined is physiological monitoring. Physiological monitoring generally involves measured signals derived from a physiological system, such as the human body. Measurements which are typically taken with physiological monitoring systems include electrocardiographs, blood pressure, blood gas saturation (such as oxygen saturation), capnographs, other blood constituent monitoring, heart rate, respiration rate, electro-encephalograph (EEG) and depth of anesthesia, for example. Other types of measurements include those which measure the pressure and quantity of a substance within the body such as cardiac output, venous oxygen saturation, arterial oxygen saturation, bilirubin, total hemoglobin, breathalyzer testing, drug testing, cholesterol testing, glucose testing, extra vasation, and carbon dioxide testing, protein testing, carbon monoxide testing, and other in-vivo measurements, for example. Complications arising in these measurements are often due to motion of the patient, both external and internal (muscle movement, vessel movement, and probe movement, for example), during the measurement process.

Many types of physiological measurements can be made by using the known properties of energy attenuation as a selected form of energy passes through a medium.

A blood gas monitor is one example of a physiological monitoring system which is based upon the measurement of energy attenuated by biological tissues or substances. Blood gas monitors transmit light into the test medium and measure the attenuation of the light as a function of time. The output signal of a blood gas monitor which is sensitive to the arterial blood flow contains a component which is a waveform representative of the patient's arterial pulse. This type of signal, which contains a component related to the patient's pulse, is called a plethysmographic wave, and is shown in FIG. 1 as curve s. Plethysmographic waveforms are used in blood gas saturation measurements. As the heart beats, the amount of blood in the arteries increases and decreases, causing increases and decreases in energy attenuation, illustrated by the cyclic wave s in FIG. 1.

Typically, a digit such as a finger, an ear lobe, or other portion of the body where blood flows close to the skin, is employed as the medium through which light energy is transmitted for blood gas attenuation measurements. The finger comprises skin, fat, bone, muscle, etc., shown schematically in FIG. 2, each of which attenuates energy incident on the finger in a generally predictable and constant manner. However, when fleshy portions of the finger are compressed erratically, for example by motion of the finger, energy attenuation becomes erratic.

An example of a more realistic measured waveform S is shown in FIG. 3, illustrating the effect of motion. The primary plethysmographic waveform portion of the signal s is the waveform representative of the pulse, corresponding to the sawtooth-like pattern wave in FIG. 1. The large, secondary motion-induced excursions in signal amplitude obscure the primary plethysmographic signal s. Even small variations in amplitude make it difficult to distinguish the primary signal component s in the presence of a secondary signal component n.

A pulse oximeter is a type of blood gas monitor which non-invasively measures the arterial saturation of oxygen in the blood. The pumping of the heart forces freshly oxygenated blood into the arteries causing greater energy attenuation. As well understood in the art, the arterial saturation of oxygenated blood may be determined from the depth of the valleys relative to the peaks of two plethysmographic waveforms measured at s