United States Patent
`Diab et al.
`
`[1] Patent Number:
`[45] Date of Patent:
`
`5,632,272
`May 27, 1997
`
`[75]
`
`[54] SIGNAL PROCESSING APPARATUS
`-
`Inventors: Mohamed K. Diab; Esmaiel
`Kiani-Azarbayjany; Ibrahim M.
`Elfadel, all of Laguna Niguel; Rex J.
`McCarthy, Mission Viejo; Walter M.
`.
`Weber, Los Angeles; Robert A. Smith,
`Corona,all of Calif.
`.
`[73] Assignee: Masimo Corporation, Mission Viejo,
`Calif.
`
`.
`
`.
`
`9/1989 Stone et al.
`4,869,254
`11/1989 Hausman .
`4,883,353
`1/1990 Cheungetal. .
`4,892,101
`3/1990 Muz.
`4,907,594
`at900 Sercmanot al. .
`too364
`ga etal. .
`yank
`5/1990 Goodman etal. .
`4,928,692
`8/1990 Lehman .
`4.948.248
`9/1990 Hall .
`4,955,379
`9/1990 Zurek et al.
`4,956,867
`.
`10/1991 Hirao et al.
`5,057,695
`5,273,036 12/1993 Kronbergetal. .
`5,458,128
`10/1995 Polanyi et al. ousseesen 128/633 X
`OTHER PUBLICATIONS
`[21] Appl. No.: 320,154
`Rabiner, Lawrenceet al. Theory and Application of Digital
`[22] Filed:
`Oct. 7, 1994
`Signal Processing, p.260, 1975,
`.
`Related U.S. Application Data
`Tremper, Kevin et al., Advances in Oxygen Monitoring, pp.
`137-153, 1987.
`[63] Continuation-in-part of Ser. No. 132,812, Oct. 6, 1993, Pat,
`Harris, Fred etal., “Digital Signal Processing with Efficient
`No. 7,490,505,and a continuation-in-partofSer. No. 249,
`‘
`2
`-
`99
`_
`,
`May
`26,
`,
`Pat.
`No.
`5,482,036, which
`1s a continu-
`Polyphase Recursive All-Pass Filters”,Presented at Inter
`ation of Ser. No. 666,060, Mar. 7, 1991, abandoned.
`national Conference on Signal Processing, Florence, Italy,
`
`[51] Tint, CUS.ccceeesessssssssssssssssssssesseeecescerssssnssoreees AGIB 5/00~—-Sep. 4-6, 1991, 6 pages.
`
`[52] U.S. Che ecsssssssessssvsssesosesssssssessnnsessses 128/633; 128/666
`(List
`continued
`t
`[58] Field of Searchy ccessscssnsccsccsrsssesee 128/633-634,
`ist continued on next page.)
`128/664-667, 672, 687-688, 716; 356/39-41
`Primary Examiner—Angela D. Sykes
`Attorney, Agent, or Firm—Knobbe, Martens, Olson & Bear,
`LLP.
`
`[56]
`
`References Cited
`
`U.S. PATENT DOCUMENTS
`
`[57]
`
`ABSTRACT
`
`3/1972 Lavallee .
`3,647,299
`3,704,706 12/1972 Herczfeld et al. .
`108615 3/1978 Kollre all
`#098117
`6/1978 Na sky et
`al.
`.
`4.407.290 10/1983 Wilber ;
`4.537.200
`8/1985 Widrow .
`4,649,505
`3/1987 Zinser, Jr. et al. .
`4,773,422
`9/1988 Isaacson etal. .
`4,799,493
`1/1989 DeFault .
`4,800,495
`1/1989 Smith .
`.
`eee qjon mck ‘ al.
`848,
`ood,
`Jr.
`.
`4,860,759
`8/1989 Kabnetal..
`4,863,265
`9/1989 Flower etal. .
`4,867,571
`9/1989 Frick et al.
`.
`4,869,253
`9/1989 Craig, Jr. et al.
`
`.
`
`The present invention involves method and apparatus for
`analyzing two measured signals that are modeled as con-
`taining 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 involvesutilizing a transformation which evalu-
`ates 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
`:
`.
`a.
`.
`;
`2 particular detail with respect to blood oximetry measure
`ens.
`
`23 Claims, 37 Drawing Sheets
`
`bee
`
`g
`
`
`
`
`
`
`800
`_
`i“ ___ _ SENSOR
`pot cSeeee mmm 7 oe
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`yeOT So O an|AO aa 7 < \
`
`
`
`
`FRONT END:
`
`ANALOG TO
`ANALOG
` HEART RATE
`DIGITAL SIGNAL PROCESSING
`y
`DIGITAL
`
`SIGNAL
`
`
`PLETHYSMOGRAPHIC.
`CONVERSION
`
`
`AND SIGNAL EXTRACTION DISPLA
`CONDITIONING
`
`
`WAVEFORM
`
`I||t
`
`{!|
`
`
`
`DIGITAL TO
`EMITTER CURRENT
`
`
`ANALOG
`DRIVERS
`
`EMITTER CURRENT
`CONVERSION
`
`CONTROL
`
`
`APPLE 1007
`
`1
`
`APPLE 1007
`
`

`

`5,632,272
`Page 2
`
`OTHER PUBLICATIONS
`
`Haykin, Simon, Adaptive Filter Theory, Prentice Hall,
`Englewood Cliffs, NJ, 1985.
`Widrow, Bernard, Adaptive Signal Processing, Prentice
`Hall, Englewood Cliffs, NJ 1985.
`Brown, David P., “Evaluation of Pulse Oximeters using
`Theoretical Models and Experimental Studies”, Master’s
`thesis, University of Washington, Nov. 25, 1987, pp. 1-142.
`Cohen, Arnon, “Volume I Time and Frequency Domains
`Analysis”, Biomedical Signal Processing, CRC Press, Inc.,
`jBoca Raton, Florida, pp. 152-159.
`Severinghaus,J.W., “Pulse Oximetry Uses and Limitations”,
`pp. 14, ASA Convention, New Orleans, 1989.
`
`Mook, G.A., et al., “Spectrophotometire determination of
`Oxygen saturation of blood independent of the presence of
`indocyanine green”, Cardiovascular Research, vol. 13, pp.
`233-237, 1979.
`Neuman, Michael R., “Pulse Oximetry: Physical Principles,
`Technical Realization and Present Limitations”, Continuous
`Transcutaneous Monitoring, Plenum Press, New York,
`1987, pp. 135-144.
`Mook, G.A., et al., “Wavelength dependency of the spec-
`trophotometric determination of blood oxygen saturation”,
`Clinical Chemistry Acta, vol. 26, pp. 170-173, 1969.
`Klimasauskas, Casey, “Neural Nets and NoiseFiltering”, Dr.
`Dobb’s Journal, Jan. 1989, p. 32.
`Melnikof, S. “Neural Networks for Signal Processing: A
`Case Study”, Dr. Dobbs Journal, Jan. 1989. pp. 36-37.
`
`2
`
`

`

`U.S. Patent
`
`May 27,1997
`
`_——
`
`Sheet 1 of 37
`
`5,632,272
`
`I
`
`FIG. 1
`
`
`
`BONE
`
`MUSCLE
`
`TISSUE
`ARTERIAL BLOOD
`
`VENOUS BLOOD
`
`
`FIG. 2
`
`FIG. 3
`
`
`
`3
`
`

`

`USS. Patent
`
`May27, 1997
`
`Sheet 2 of 37
`
`5,632,272
`
`226
`
`246
`
`20
`
`Ab
`
`“Ab
`
` S =S§,,.¢n “Ab
`
`SIGNAL
`CONDITIONER
`
` DISPLAY
`
`CORRELATION
`CANCELER
`
`S)a(t)
`
`FIG. 4a
`
`
`
`SIGNAL
`CONDITIONER
`
`L220
`
`
`
`4
`
`

`

`USS. Patent
`
`May27, 1997
`
`Sheet 3 of 37
`
`5,632,272
`
`20
`
`246
`Sy.=5,.4n
`Ab
`“Ab
`“Ab
`
`220
`
`
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`
` DISPLAY
`CORRELATION
`
`CANCELER
`Nya(t)
`
`FIG. 4b
`
`5
`
`

`

`U.S. Patent
`
`May27, 1997
`
`Sheet 4 of 37
`
`5,632,272
`
`J0
`
`™
`S){0= Sy {o + nyA(t)
`
`
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`
`FIG. 5a
`
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`
`50
`
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`8,d0=s,0 +n)(H)
`
`S,f0=sa? +nay
`
`OR ny fv) OR ny
`
`FIG. 5b
`
`6
`
`

`

`U.S. Patent
`
`May27, 1997
`
`Sheet 5 of 37
`
`5,632,272
`
`
`
`TRANSFERFUNCTION
`
`FREQUENCY(f)
`
`FIG.5¢c
`
`7
`
`

`

`U.S. Patent
`
`May27, 1997
`
`Sheet 6 of 37
`
`
`
`
`5,632,272
`
`
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`

`

`US.
`
`Patent
`
`May 27, 1997
`
`Sheet 7 of 37
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`US. Patent
`
`May27, 1997
`
`Sheet 8 of 37
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`5,632,272
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`US. Patent
`
`May 27, 1997
`
`Sheet 9 of 37
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`

`U.S. Patent
`
`May27, 1997
`
`Sheet 10 of 37
`
`5,632,272
`
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`U.S. Patent
`
`May27, 1997
`
`Sheet 11 of 37
`
`5,632,272
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`US. Patent
`
`May27, 1997
`
`Sheet 12 of 37
`
`5,632,272
`
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`

`

`U.S. Patent
`
`May27, 1997
`
`Sheet 13 of 37
`
`5,632,272
`
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`15
`
`

`

`U.S. Patent
`
`May27, 1997
`
`Sheet 14 of 37
`
`5,632,272
`
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`May 27, 1997
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`US. Patent
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`May 27, 1997
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`Sheet 16 of 37
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`May27, 1997
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`U.S. Patent
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`May27, 1997
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`Sheet 28 of 37
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`May 27, 1997
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`Sheet 29 of 37
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`5,632,272
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`May 27, 1997
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`5,632,272
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`SATURATION
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`U.S. Patent
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`May27, 1997
`
`Sheet 31 of 37
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`NUMBER OF OCCURENCES |
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`U.S. Patent
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`May27, 1997
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`Sheet 32 of 37
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`5,632,272
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`May27, 1997
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`Sheet 35 of 37
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`U.S. Patent
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`May 27, 1997
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`Sheet 36 of 37
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`5,632,272
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`U.S. Patent
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`May 27
`
`» 1997
`
`Sheet 37 of 37
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`5,632,272
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`5,632,272
`
`1
`SIGNAL PROCESSING APPARATUS
`
`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,
`
`ra0
`
`BACKGROUND OF THE INVENTION
`1. Field of the Invention
`
`The present invention relates to the field of signal pro-
`cessing. 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 por-
`tion and a secondary signal portion. For example, a com-
`posite 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 thetotal 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 portionsexists.
`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 removeeither 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
`
`30
`
`40
`
`45
`
`50
`
`60
`
`40
`
`2
`corresponding primary or secondary signal portions, they
`have a frequency spectrum which is similar to that of the
`primary or secondary signal portions.
`Jn many cases, nothing or verylittle 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. Physi-
`ological monitoring generally involves measured signals
`derived from a physiological system, such as the human
`body. Measurements which are typically taken with physi-
`ological 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 mea-
`sure the attenuation of the light as a function of time. The
`output signal of a blood gas monitor whichis sensitive to the
`arterial blood flow contains a component which is a wave-
`form 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 sche-
`matically in FIG. 2, each of which attenuates energy incident
`on thefinger in a generally predictable and constant manner.
`However, whenfleshy portions of the finger are compressed
`erratically, for example by motion of the finger, energy
`attenuation becomeserratic.
`
`An example of a morerealistic 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 components in the presence of a secondary
`signal componentn.
`A pulse oximeter is a type of blood gas monitor which
`non-invasively measures the arterial saturation of oxygen in
`
`40
`
`

`

`5,632,272
`
`3
`the blood. The pumping of the heart forces freshly oxygen-
`ated blood into the arteries causing greater energy attenua-
`tion. 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 wave-
`forms measured at separate wavelengths. Patient movement
`introduces motion artifacts to the composite signal as illus-
`trated in the plethysmographic waveform illustrated in FIG.
`3. These motionartifacts distort the measured signal.
`
`SUMMARY OF THE INVENTION
`
`This invention provides improvements upon the methods
`and apparatus disclosed in U.S. patent application Ser. No.
`08/132.812, filed Oct. 6, 1993, entitled Signal Processing
`Apparatus, which earlier application has been assigned to
`the assignee of the instant application. The present invention
`involves several different embodiments using the novel
`signal model in accordance with the present invention to
`isolate either a primary signal portion or a secondary signal
`portion of a composite measured signal. In one embodiment,
`a signal processor acquires a first measured signal and a
`second measured signal that is correlated to the first mea-
`sured signal. Thefirst signal comprises a first primary signal
`portion and a first secondary signal portion. The second
`signal comprises a second primary signal portion and a
`second secondary signal portion. The signals may be
`acquired by propagating energy through a medium and
`measuring an attenuated signal after transmission or reflec-
`tion. Alternatively, the signals may be acquired by measur-
`ing energy generated by the medium.
`In one embodiment, the first and second measured signals
`are processed to generate a secondary reference which does
`not contain the primary signal portions from either of the
`first or second measured signals. This secondary referenceis
`correlated to the secondary signal portion of each of thefirst
`and second measured signals. The secondary reference is
`used to remove the secondary portion of eachof the first and
`second measured signals via a correlation canceler, such as
`an adaptive noise canceler. The correlation canceler is a
`device which takes a first and second input and removes
`from the first inputall signal components which are corre-
`lated to the second input. Any unit which performs or nearly
`performs this function is herein considered to be a correla-
`tion canceler.
`
`An adaptive correlation canceler can be described by
`analogy to a dynamic multiple notch filter which dynami-
`cally changesits transfer function in response to a reference
`signal and the measuredsignals to remove frequencies from
`the measured signals that are also present in the reference
`signal. Thus, a typical adaptive correlation canceler receives
`the signal from whichit is desired to remove a component
`and receives a reference signal of the undesired portion. The
`outputof the correlation canceler is a good approximation to
`the desired signal with the undesired component removed.
`Alternatively, the first and second measured signals may
`be processed to generate a primary reference which does not
`contain the secondary signal portions from eitherof the first
`or second measured signals. The primary reference may then
`be used to removethe primary portion of each of thefirst and
`second measured signals via a correlation canceler. The
`outputof the correlation canceler is a good approximation to
`the secondary signal with the primary signal removed and
`may be used for subsequent processing in the same instru-
`ment or an auxiliary instrument. In this capacity,
`the
`approximation to the secondary signal may be used as a
`reference signal for input to a second correlation canceler
`
`4
`together with either the first or second measured signals for
`computation of, respectively, either the first or second pri-
`mary signal portions.
`Physiological monitors can benefit from signal processors
`of the present invention. Often in physiological measure-
`ments a first signal comprising a first primary portion and a
`first secondary portion and a second signal comprising a
`second primary portion and a second secondary portion are
`acquired. The signals may be acquired by propagating
`energy through a patient’s body (or a material which is
`derived from the body, such as breath, blood, or tissue, for
`example) or inside a vessel and measuring an attenuated
`signal after transmission or reflection. Alternatively,
`the
`signal may be acquired by measuring energy generated by a
`patient’s body, such as in electrocardiography. The signals
`are processed via the signal processor of the present inven-
`tion to acquire either a secondary reference or a primary
`reference whichis input to a correlation canceler, such as an
`adaptive noise canceler.
`One physiological monitoring apparatus which benefits
`from the present invention is a monitoring system which
`determines a signal which is representative of the arterial
`pulse, called a plethysmographic wave. This signal can be
`used in blood pressure calculations, blood constituent
`measurements, etc. A specific example of such a useis in
`pulse oximetry. Pulse oximetry involves determining the
`saturation of oxygen in the blood. In this configuration, the
`primary portion of the signal is the arterial blood contribu-
`tion to attenuation of energy as it passes through a portion
`of the body where blood flows close to the skin. The
`pumping of the heart causes blood flow to increase and
`decrease in the arteries in a periodic fashion, causing peri-
`odic attenuation wherein the periodic waveform is the
`plethysmographic waveform representative of the arterial
`pulse. The secondary portion is noise. In accordance with the
`present invention, the measured signals are modeled such
`that this secondary portion of the signal is related to the
`venous blood contribution to attenuation of energy as it
`passes through the body. The secondary portion also
`includes artifacts due to patient movement which causes the
`venous blood to flow in an unpredictable manner, causing
`unpredictable attenuation and corrupting the otherwise peri-
`odic plethysmographic waveform. Respiration also causes
`the secondary or noise portion to vary, although typically at
`a lower frequency than the patients pulse rate. Accordingly.
`the measured signal which forms a plethysmographic wave-
`form is modeled in accordance with the present invention
`such that the primary portion ofthe signal is representative
`of arterial blood contribution to attenuation and the second-
`ary portion is due to several other parameters.
`A physiological monitor particularly adapted to pulse
`oximetry oxygen saturation measurement comprises two
`light emitting diodes (LED’s) which emitlight at different
`wavelengths to producefirst and second signals. A detector
`registers the attenuation of the two different energy signals
`after each passes through an absorptive media, for example
`a digit such as a finger. or an earlobe. The attenuated signals
`generally comprise both primary (arterial attenuator) and
`secondary (noise) signal portions. A static filtering system,
`such as a bandpassfilter, removesa portion of the secondary
`signal which is outside of a known bandwidth of interest,
`leaving an erratic or random secondary signal portion, often
`caused by motion and often difficult to remove, along with
`the primary signal portion.
`A processor in accordance with one embodiment of the
`present invention removes the primary signal portions from
`the measured signals yielding a secondary reference which
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`is a combination of the remaining secondary signal portions.
`The secondary reference is correlated to both of the second-
`ary signal portions. The secondary reference and at least one
`of the measured signais are input to a correlation canceler,
`such as an adaptive noise canceler, which removes the
`random or erratic portion of the secondary signal. This
`yields a good approximation to a primary plethysmographic
`signal as measured at one of the measured signal wave-
`lengths. As is knownin the art, quantitative measurements of
`the amount of oxygenated arterial blood in the body can be
`determined from the plethysmographic signal in a variety of
`ways.
`The processor of the present invention may also remove
`the secondary signal portions from the measured signals
`yielding a primary reference which is a combination of the
`remaining primary signal portions. The primary referenceis
`correlated to both of the primary signal portions. The
`primary reference and at least one of the measured signals
`are input to a correlation canceler which removes the pri-
`Iuary portions of the measured signals. This yields a good
`approximation to the secondary signal at one of the mea-
`sured signal wavelengths. This signal may be useful for
`removing secondary signals from an auxiliary instrumentas
`well as determining venous blood oxygen saturation.
`In accordance with the signal model of the present
`invention, the two measured signals each having primary
`and secondary signal portions can be related by coefficients.
`By relating the two equations with respect to coefficients
`defined in accordance with the present invention, the coef-
`ficients provide information about the arterial oxygen satu-
`ration and aboutthe noise (the venous oxygen saturation and
`other parameters). In accordance with this aspect of the
`present invention, the coefficients can be determined by
`minimizing the correlation between the