US006081735A
`6,081,735
`(114) Patent Number:
`United States Patent 55
`Diabet al.
`[45] Date of Patent:
`*Jun. 27, 2000
`
`
`[54]
`
`SIGNAL PROCESSING APPARATUS
`
`[75]
`
`Inventors: Mohamed K. Diab; Massi E. Kiani;
`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,Irvine, Calif.
`[*] Notice:
`This patent is subject to a terminal dis-
`claimer.
`
`[21] Appl. No.: 08/887,815
`[22]
`Filed:
`Jul. 3, 1997
`
`4/1989 Frick etal. .
`4,824,242
`7/1989 Hood, Jr.
`.
`4,848,901
`8/1989 Kahnetal. .
`4,860,759
`9/1080 poweretal
`103.200
`9/1980 Cai
`“heotal
`4860253
`91989 Slone ot ‘al
`4869254
`4883353 11/1989 Hausman -_
`tod 1000 enne etal. .
`(List continued on next page.)
`FOREIGN PATENT DOCUMENTS
`1674798
`9/1991 USSR...
`92/15955
`9/1992 WIPO.
`
`Related U.S. Application Data
`[63] Continuation of application No. 08/859,837, May 16, 1997,
`whichis a continuation of application No. 08/320,154, Oct.
`7, 1994, Pat. No. 5,632,272, which is a continuation-in-part
`of application No. 08/132,812, Oct. 6, 1993, Pat. No.
`5,490,505.
`Int. Cl.’ dee eeee eee nen een eee eee eeee nen eee eee een ene eeee eee eee eee ee A61B 5/00
`
`[51]
`
`OTHER PUBLICATIONS
`of
`Jingzheng, Ouyang
`et
`al.,
`. Digital Processing
`of
`High-Resolution
`Electrocardiograms—Detection
`His—Purkinje Activity from the Body Surface”, Biomediz-
`inische Technik, 33, Oct. 1, 1988, No. 10, Berlin, W.
`Germany, pp. 224—230.
`(List continued on next page.)
`
`[52] U.S. Ch. ceceeeeeeee 600/336; 600/481; 600/508;
`600/529
`[58] Field of Search occ 600/300, 322,
`600/323, 330, 336, 473, 476, 481, 500
`
`, 508, 509, 529
`
`[56]
`
`,
`,
`1323,
`References Cited
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`3/1972 Lavallee .
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`
`.
`
`Primary Examiner—Exic F. Winakur
`Attorney, Agent, or Firm—Knobbe, Martens, Olson & Bear,
`LLP
`
`ABSTRACT
`[57]
`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 involves utilizing a transformation which evalu-
`ates a plurality of possible signal coefficients in orderto 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 measure-
`ments.
`
`28 Claims, 37 Drawing Sheets
`
`
`SIGNAL
`
`CONDITIONER
`
`
`SF Srat Pag
`
`
`
`Pav)
`Shalt)
`
`2B
`
`DISPLAY
`alt)
`
`“S
`
`n(t)= ny,(t) - tanyp(t)
`LF
`
`CORRELATION
`CANCELER
`
`1
`
`APPLE 1030
`
`
`
`1
`
`APPLE 1030
`
`

`

`6,081,735
`
`Page 2
`
`U.S. PATENT DOCUMENTS
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`
`3/1990 Corenmanet al.
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`4,948,248
`9/1990 Hall .
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`.
`9/1990 Zurek et al.
`4,956,867
`10/1990 Conlonetal. .
`4,960,126
`10/1991 Hiraoetal. .
`5,057,695
`9/1993 Prosser.
`5,246,002
`.
`12/1993 Kronberget al.
`5,273,036
`7/1995 Mathews oo. cceeeeeseceeceeeeneee 600/323
`5,431,170
`5,458,128 10/1995 Pulanyi etal. .
`5,632,272
`5/1997 Diab et ab. oo eee ceeteeee 600/323
`
`OTHER PUBLICATIONS
`
`Chen, Jiande, et al., “Adaptive System for Processing of
`Electrogastric Signals”, Images of the Twenty-First Cen-
`tury, Seattle, WA, vol. 11, Nov. 9-12, 1989. pp. 698-699.
`Varanini, M. et al., “A Two Channel Adaptive Filtering
`Approach for Recognition of the QRS Morphology”, Pro-
`ceedings of the Computers in Cardiology Meeting, Venice,
`Sep. 23-26, 1991, Institute of Electrical and Electronics
`Engineers, pp. 141-144.
`Rabiner, Lawrence et al. Theory and Application of Digital
`Signal Processing, p. 260, 1975.
`Tremper, Kevin et al., Advances in Oxygen Monitoring, pp.
`137-153, 1987.
`Harris, Fred etal., “Digital Signal Processing with Efficient
`Polyphase Recursive All—Pass Filters”, Presented at Inter-
`national Conference on Signal Processing, Florence, Italy,
`Sep. 4-6, 1991, 6 pages.
`
`Haykin, Simon, Adaptive Filter Theory, Prentice Hall,
`Englewood Cliffs, NJ, 1991.
`
`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.,
`Boca Raton, Florida, pp. 152-159.
`
`Severinghaus, J.W., “Pulse Oximetry Uses and Limitations”,
`pp. 1-4, ASA Convention, New Orleans, 1989.
`
`Mook, G.A., et al., “Spectrophotometric 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 Noise Filtering”, Dr.
`Dobb’s Journal, Jan. 1989, p. 32.
`
`Melnikof, S. “Neural Networks for Signal Processing: A
`Case Study”, Dr. Dobbs Journal, Jan. 1989. p. 36-37.
`
`2
`
`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 1 of 37
`
`6,081,735
`
`I
`
`FIG. 1
`
`
`
`BONE
`
`MUSCLE
`
`TISSUE
`
`ARTERIAL BLOOD
`
`VENOUS BLOOD
`
`FIG. 2
`
`
`
`3
`
`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 2 of 37
`
`6,081,735
`
` DISPLAY
`
`CORRELATION
`CANCELER
`
`S\a(t)
`
`FIG. 4a
`
`4
`
`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 3 of 37
`
`6,081,735
`
` DISPLAY
`
`CORRELATION
`CANCELER
`
`n>a(t)
`
`FIG. 4b
`
`5
`
`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 4 of 37
`
`6,081,735
`
`JO
`
`_
`Sy,f= S) ft) +nralt)
`OR
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`cat)
`
`ndAt) OR n>ib)
`
`
`
`FIG. 56
`
`6
`
`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 5 of 37
`
`6,081,735
`
`
`
`NOILONN4YdsSNVaL
`
`FREQUENCY(f)
`
`FIG.5c
`
`7
`
`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 6 of 37
`
`6,081,735
`
`
`
`
`
`
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`i
`
`8
`
`

`

`U.S. Patent
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`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 8 of 37
`
`6,081,735
`
`FIG.7b
`
`T10
`
`
`
`SIGNALCOEFFICIENTS
`
`RELATIVE CORRELATION CANCELER
`ENERGY OUTPUT
`
`10
`
`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 9 of 37
`
`6,081,735
`
`mal
`
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`
`SIGNALCOEFFICIENTS
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`RELATIVE CORRELATION CANCELER
`ENERGY OUTPUT
`
`11
`
`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 10 of 37
`
`6,081,735
`
`LEAST SQUARES LATTICE
`PREDICTOR
`
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`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 11 of 37
`
`6,081,735
`
`QRD-—LSL PREDICATOR
`
`QRD-LSL FILTER
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`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 12 of 37
`
`6,081,735
`
`120
`
`INITIALIZE NOISE
`CANCELLER
`
`130
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`INPUT NEW SAMPLES
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`14
`
`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 13 of 37
`
`6,081,735
`
`120g
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`
`15
`
`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 14 of 37
`
`6,081,735
`
`LEAST SQURES LATTICE
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`

`

`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 15 of 37
`
`6,081,735
`
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`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 16 of 37
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`6,081,735
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`U.S. Patent
`
`Jun. 27, 2000
`
`Sheet 17 of 37
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`6,081,735
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`U.S. Patent
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`Jun. 27, 2000
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`Sheet 18 of 37
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`Jun. 27, 2000
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`Sheet 19 of 37
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`Jun. 27, 2000
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`Jun. 27, 2000
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`U.S. Patent
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`Jun. 27, 2000
`
`Sheet 23 of 37
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`6,081,735
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`1
`SIGNAL PROCESSING APPARATUS
`
`REFERENCE TO PRIOR RELATED
`APPLICATION
`
`This is a continuation of application of U.S. patent
`application Ser. No. 08/859,837 filed May 16, 1997, which
`is a continuation of application of U.S. patent application
`Ser. No. 08/320,154 filed Oct. 7, 1994, now U.S. Pat. No.
`5,632,272 whichis a c-i-p of U.S. patent application Ser. No.
`08/132,812 filed Oct. 6, 1993, now USS. Pat. No. 5,490,505.
`
`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. Moreparticularly, 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 oxygensaturation 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
`primaryor the secondarysignal 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 cancilers, 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
`
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`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. 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 measurementprocess.
`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 measurementof
`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 whichissensitive 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 flowsclose 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, when fleshy portions of the finger are compressed
`erratically, for example by motion of the finger, energy
`attenuation becomeserratic.
`
`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 makeit 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 measuresthe arterial saturation of oxygen in
`
`40
`
`

`

`SUMMARYOF THE INVENTION
`
`6,081,735
`
`10
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`together with eitherthe first or second measured signals for
`the blood. The pumping ofthe heart forces freshly oxygen-
`computation of, respectively, either the first or second pri-
`ated blood into the arteries causing greater energy attenua-
`mary signal portions.
`tion. As well understood in the art, the arterial saturation of
`Physiological monitors can benefit from signal processors
`oxygenated blood may be determined from the depth of the
`of the present invention. Often in physiological measure-
`valleys relative to the peaks of two plethysmographic wave-
`mentsafirst signal comprisingafirst primary portion and a
`forms measured at separate wavelengths. Patient movement
`first secondary portion and a second signal comprising a
`introduces motionartifacts to the composite signal as illus-
`second primary portion and a second secondary portion are
`trated in the plethysmographic waveform illustrated in FIG.
`acquired. The signals may be acquired by propagating
`3. These motion artifacts distort the measured signal.
`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 use is 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
`includesartifacts due to patient movement which causesthe
`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 of the signal is representative
`of arterial blood contribution to attenuation and the second-
`
`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. The first signal comprisesa 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 orreflec-
`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 reference is
`correlated to the secondary signal portion of each of the first
`and second measured signals. The secondary reference is
`used to remove the secondary portion of each of 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 input all signal components which are corre-
`lated to the second input. Any unit which performsor nearly
`performsthis 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 changes its transfer function in response to a reference
`signal and the measured signals to remove frequencies from
`ary portion is due to several other parameters.
`the measured signals that are also present in the reference
`signal. Thus, a typical adaptive correlation canceler receives
`A physiological monitor particularly adapted to pulse
`the signal from which it is desired to remove a component
`oximetry oxygen saturation measurement comprises two
`and receives a reference signal of the undesired portion. The
`light emitting diodes (LED’s) which emit light at different
`output of the correlation canceler is a good approximation to
`wavelengths to produce first and second signals. A detector
`the desired signal with the undesired component removed.
`registers the attenuation of the two different energy signals
`after each passes through an absorptive media, for example
`Alternatively, the first and second measured signals may
`a digit such asafinger, or an earlobe. The attenuated signals
`be processed to generate a primary reference which does not
`generally comprise both primary (arterial attenuator) and
`contain the secondary signal portions from eitherof the first
`secondary (noise) signal portions. A static filtering system,
`or second measured signals. The primary reference may then
`such as a bandpassfilter, removes a portion of the secondary
`be used to removethe primary portion of each ofthefirst and
`signal which is outside of a known bandwidth of interest,
`second measured signals via a correlation canceler. The
`leaving an erratic or random secondary signal portion, often
`output of the correlation canceler is a good approximation to
`caused by motion and often difficult to remove, along with
`the secondary signal with the primary signal removed and
`the primary signal portion.
`may be used for subsequent processing in the same instru-
`ment or an auxiliary instrument.
`In this capacity,
`the
`A processor in accordance with one embodiment of the
`approximation to the secondary signal may be used as a
`present invention removesthe primary signal portions from
`reference signal for input to a second correlation canceler
`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 andat least one
`of the measured signals 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 signalin 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 reference is
`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 removesthe pri-
`mary 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 instrument as
`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 oxygensaturation and
`other parameters). In accordance with this aspect of the
`present invention,
`the coefficients can be determined by
`minimizing the correlation between the primary and sec-
`ondary sig